Video library

Relational fundamentals, performance, transactions, and scaling.Not startedEnglishDatabasesDistributed systems

13 Database Concepts Every Backend Engineer Must Know

Amigoscode · 13:17

Deploying real applications on a small AWS budget.Not startedEnglishSystem designCloud

50 Million HTTP Requests/Month ($15 Budget) [First 2 Hours]

Cododev · 2:26:15

Advanced Algorithms (COMPSCI 224), Lecture 1

The opening lecture of Harvard's CS224 covers course logistics, then immediately attacks the belief that sorting cannot beat n log n — showing that bound only holds in the comparison model, which real machines don't obey. The lecture introduces the word-RAM model (integers in [0, 2^w), all C-style bit and...Not startedEnglishAlgorithmsCourses

Harvard University · 1:28:19

Advanced Algorithms (COMPSCI 224), Lecture 2

A full lecture on fusion trees (Fredman–Willard), the Word-RAM data structure that answers static predecessor queries in O(log_w n) time. After a short erratum about the van Emde Boas space argument from lecture 1, the lecture builds a Θ(w^(1/5))-ary search tree whose height is O(log_w n), then spends the rest of...Not startedEnglishAlgorithmsCourses

Harvard University · 1:25:39

Advanced Algorithms (COMPSCI 224), Lecture 3

A Harvard graduate lecture on hashing in the word RAM model. It starts with hashing as load balancing — the balls-and-bins process — proving that n jobs hashed to n machines leave no machine with more than O(log n / log log n) jobs, first via the Chernoff bound and then via a much simpler union-bound argument. That...Not startedEnglishAlgorithmsCourses

Harvard University · 1:28:46

Advanced Algorithms (COMPSCI 224), Lecture 4

The last lecture devoted exclusively to hashing. It opens by repairing a lemma about linear probing from the previous class, then shows how the moment-method analysis works — first with 7-wise independence via a symmetrization trick, then with only 5-wise independence via the Pagh–Pagh–Ružić binary-tree argument...Not startedEnglishAlgorithmsCourses

Harvard University · 1:27:51

Advanced Algorithms (COMPSCI 224), Lecture 5

The lecture that closes out hashing in COMPSCI 224. The first half completes the expected-O(1) insertion proof for cuckoo hashing: it recalls the scheme (two hash functions, unconditional placement, cascading evictions, rebuild after C log n steps), models an insertion as a walk in the cuckoo graph, splits it into...Not startedEnglishAlgorithmsCourses

Harvard University · 1:21:37

Advanced Algorithms (COMPSCI 224), Lecture 6

This lecture leaves the word RAM model behind and opens the course's unit on amortized analysis, introducing the potential function method and then applying it to priority queues. It builds binomial heaps as a warm-up — a forest of one tree per rank behaving like a binary counter — proves constant amortized...Not startedEnglishAlgorithmsCourses

Harvard University · 1:23:46

Advanced Algorithms (COMPSCI 224), Lecture 7

A university lecture (Harvard COMPSCI 224, Advanced Algorithms) devoted entirely to splay trees — Sleator and Tarjan's self-adjusting binary search tree — as a second worked example of amortized analysis for a data structure. The first half is a survey: the BST model, how find/insert/delete are built on top of a...Not startedEnglishAlgorithmsCourses

Harvard University · 1:26:46

Advanced Algorithms (COMPSCI 224), Lecture 8

An introduction to online algorithms and competitive analysis: how to make irrevocable decisions without knowing the future, and how to prove you never spend much more than an omniscient optimum. After two warm-up examples (ski rental, searching a hallway), the lecture works through the two problems Sleator and...Not startedEnglishAlgorithmsCourses

Harvard University · 1:24:06

Advanced Algorithms (COMPSCI 224), Lecture 9

A university lecture in two halves. The first half completes the analysis of MARK, the randomized paging algorithm of Fiat et al., proving it is 2·H_K competitive via a phase-based argument on "clean" and "stale" pages, then proving a matching-up-to-constants Ω(log K) lower bound for any paging algorithm using a...Not startedEnglishAlgorithmsCourses

Harvard University · 1:24:56

Advanced Algorithms (COMPSCI 224), Lecture 10

This lecture closes out the primal-dual method for online algorithms with two full worked examples and then opens the course's next topic, approximation algorithms. The first half re-derives the classic e/(e−1) randomized bound for ski rental by building feasible primal and dual LP solutions online and then...Not startedEnglishAlgorithmsCourses

Harvard University · 1:24:33

Advanced Algorithms (COMPSCI 224), Lecture 11

A Harvard graduate lecture on LP-based approximation algorithms, in three movements. It first completes the dual fitting analysis of greedy set cover (proving an H_K bound) and gives a clean primal-dual 2-approximation for vertex cover. It then turns to the limits of the LP framework, defining the integrality gap...Not startedEnglishAlgorithmsCourses

Harvard University · 1:25:41

Advanced Algorithms (COMPSCI 224), Lecture 12

The final lecture of the approximation-algorithms block, covering three topics. First it completes the story on approximation schemes: a rounding-based FPTAS for Knapsack running in O(n³/ε), followed by bin packing as an example of a strongly NP-hard problem where no FPTAS can exist. Second it introduces FPRAS...Not startedEnglishAlgorithmsCourses

Harvard University · 1:25:04

Advanced Algorithms (COMPSCI 224), Lecture 13

A guest lecture by Rong Ge (postdoc, Microsoft Research), standing in for Jelani Nelson, on learning topic models — a case study in applying theoretical-CS algorithm design to machine learning 0:00, 0:36.Not startedEnglishAlgorithmsCourses

Harvard University · 1:21:46

Advanced Algorithms (COMPSCI 224), Lecture 15

After many lectures treating linear programming as a black box, this lecture finally opens the box and develops the Simplex algorithm from scratch. It builds the machinery in order: reducing any LP to standard form (min cᵀx, Ax = b, x ≥ 0), defining a vertex of the polytope, showing how to obtain a starting vertex...Not startedEnglishAlgorithmsCourses

Harvard University · 1:26:13

Advanced Algorithms (COMPSCI 224), Lecture 16

This lecture closes out the simplex algorithm and then surveys the polynomial-time alternatives for linear programming. It completes the reduced-cost pivot step, patches the degenerate case with Bland's rule, and uses the shadow price vector to derive strong duality and complementary slackness as corollaries of...Not startedEnglishAlgorithmsCourses

Harvard University · 1:24:57

Advanced Algorithms (COMPSCI 224), Lecture 17

A university lecture on the interior point method (IPM) for linear programming. The first half sets up the method: replace min cᵀx s.t. Ax ≥ b by the penalized objective f_λ(x) = λ·cᵀx − Σ log s(x)ᵢ, follow the resulting central path from the analytic center of the feasible region toward the optimal vertex as λ...Not startedEnglishAlgorithmsCourses

Harvard University · 1:26:44

Advanced Algorithms (COMPSCI 224), Lecture 18

This lecture completes the analysis of the interior point method (IPM) for linear programming by supplying its missing engine: Newton's method, a second-order optimization method with oracle access to f, ∇f, and ∇²f. The first half states and proves a progress theorem — if the Hessian is spectrally stable along the...Not startedEnglishAlgorithmsCourses

Harvard University · 1:24:42

Advanced Algorithms (COMPSCI 224), Lecture 19

This lecture introduces the multiplicative weights (MW) method, starting from the "listening to expert advice" problem: n experts give daily yes/no predictions and you must decide, aiming to make nearly as few mistakes as the best expert in hindsight. The lecture builds up through two warm-up algorithms...Not startedEnglishAlgorithmsCourses

Harvard University · 1:21:33

Advanced Algorithms (COMPSCI 224), Lecture 20

A two-part lecture. The first half closes out multiplicative weights by showing how it approximately solves linear programs: the m LP constraints become the "experts", a ρ-bounded oracle answers a one-constraint relaxation each day, and the average of the oracle's answers is an almost-feasible point. Fractional set...Not startedEnglishAlgorithmsCourses

Harvard University · 1:23:37

Advanced Algorithms (COMPSCI 224), Lecture 21

A lecture on faster maximum-flow algorithms, picking up from a Ford–Fulkerson recap. Jelani Nelson first fixes the vocabulary — weakly polynomial, strongly polynomial, pseudo-polynomial — and surveys the best bounds known at the time (Orlin's O(mn), Goldberg–Rao, the then-days-old Lee–Sidford interior-point...Not startedEnglishAlgorithmsCourses

Harvard University · 1:27:09

Advanced Algorithms (COMPSCI 224), Lecture 22

A lecture devoted almost entirely to link-cut trees (Sleator–Tarjan, JCSS 1983) and their use as the accelerator inside the blocking-flow max-flow algorithm. Jelani Nelson starts from the waste in the previous lecture's routine — after each augment, the plain DFS re-walks surviving path fragments from s — and...Not startedEnglishAlgorithmsCourses

Harvard University · 1:20:15

Advanced Algorithms (COMPSCI 224), Lecture 23

A lecture in two halves. First, Jelani Nelson completes the amortized analysis of link-cut trees, introducing the heavy-light decomposition purely as an accounting device: every operation's cost is charged to preferred child changes, those are charged to light preferred edge creations, and each root-to-vertex path...Not startedEnglishAlgorithmsCourses

Harvard University · 1:26:46

Advanced Algorithms (COMPSCI 224), Lecture 25

A two-part lecture that closes the exponential-time algorithms in small space thread and opens the course's final topic, streaming and sketching. The first half derives the k-colorability inclusion–exclusion formula properly: it defines the zeta transform and Möbius inversion, proves they invert each other, and...Not startedEnglishAlgorithmsCourses

Harvard University · 1:26:14

Advanced Algorithms (COMPSCI 224), Lecture 26

The final lecture of the course, which Jelani Nelson titles "the power of random signs": one object — a matrix Π whose entries are random ±1/√m — solves four apparently unrelated problems. He builds it first as the AMS sketch for estimating ‖x‖₂² in a stream, proving unbiasedness and an O(‖x‖₂⁴/m) variance so...Not startedEnglishAlgorithmsCourses

Harvard University · 1:25:02

Theo iterates on T3 Code's UI with a council of model reviewers, then applies evaluation-driven optimization to MCP tool descriptions.Not startedEnglishAI codingAgent workflowsLLM evaluation

Agents Sucked At UI (Until Today)

Theo - t3․gg · 31:44

Reusable skills, context management, and engineering fundamentals.Not startedEnglishAI codingAgent workflows

AI Skills with Matt Pocock

The Pragmatic Engineer · 1:36:36

Theo explains Claude Ultra, subscription limits, account verification, and unequal usage accounting in Claude Code and Agent SDK apps.Not startedEnglishAI codingAgent workflows

Anthropic can't stop winning

Theo - t3․gg · 16:46

Full CLF-C02 course with AWS services, labs, and exam preparation.Not startedEnglishSystem designCloud

AWS Certified Cloud Practitioner Certification Course 2026 (CLF-C02) - Pass the Exam!

freeCodeCamp.org · 13:46:27

Building OpenCode, inference economics, and engineering culture.Not startedEnglishAI codingAgent workflows

Building OpenCode with Dax Raad

The Pragmatic Engineer · 1:21:01

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#00 - Course Overview & Logistics (CMU Intro to Database Systems)

CMU Database Group · 21:20

Andy Pavlov's logistics lecture for CMU 15-445/645 (Fall 2024), recorded ahead of the semester so the first real class can start immediately on the relational model. It covers what the course actually is — building the internals of a database system, not using or administering one — and every policy that governs...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#01 - Relational Model & Algebra (CMU Intro to Database Systems)

CMU Database Group · 1:23:38

The opening technical lecture of CMU 15-445/645 (Fall 2024), taught by Andy Pavlo. It separates a database (an organized collection of data modeling the real world) from a DBMS (the software managing it), then uses a deliberately bad flat-CSV music store to enumerate every problem — scans, type errors, concurrency,...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#02 - Modern SQL (CMU Intro to Database Systems)

CMU Database Group · 1:18:44

> CMU Database Group · 1:18:44 · Watch on YouTube > Content type: university lecture (educational) — CMU 15-445/645, Fall 2024, Lecture 02.Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#03 - Database Storage: Files & Pages ✸ Neon Database Talk (CMU Intro to Database Systems)

CMU Database Group · 1:22:27

Third lecture of CMU 15-445/645 (Fall 2024), and the first one that goes inside the database engine. It builds the bottom of the storage stack from the hardware upward: why a disk-oriented DBMS exists, how the storage hierarchy and the sequential-vs-random access gap dictate design, how databases are laid out as...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#04 - Database Storage: Log-Structured Merge Trees & Tuples (CMU Intro to Database Systems)

CMU Database Group · 1:22:41

University lecture (CMU 15-445/645, Fall 2024) that finishes the tuple-oriented storage model and then presents its two main alternatives. The first half completes slotted pages and record IDs — with live demos of ctid, rowid and %%physloc%% in PostgreSQL, SQLite, SQL Server and Oracle — and enumerates the problems...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#05 - Row vs. Column Storage + Compression ✸ StarTree Database Talk (CMU Intro to Database Systems)

CMU Database Group · 1:28:00

The final lecture of CMU 15-445/645's storage-layer sequence, contrasting how a DBMS can physically lay out tuples and what that costs. Andy Pavlo first separates OLTP from OLAP workloads, then walks the same Wikipedia-derived query through the N-ary Storage Model (row store), the Decomposition Storage Model...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#06 - Memory & Disk I/O Management (CMU Intro to Database Systems)

CMU Database Group · 1:23:56

Lecture 6 of CMU 15-445/645 (Fall 2024) covers how a DBMS moves pages between disk and memory and why it must do that job itself instead of delegating it to the operating system. It builds the buffer pool manager from the ground up — frames, the page table, pins, dirty flags and latches — then argues at length...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#07 - Hash Tables ✸ RelationalAI Database Talk (CMU Intro to Database Systems)

CMU Database Group · 1:23:43

Lecture 7 of CMU 15-445/645 (Fall 2024) opens the access methods stretch of the course: with disk management and the buffer pool already built, Andy Pavlo turns to the data structures the execution engine will use, starting with the unordered one — the hash table. The lecture decomposes a hash table into two...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#08 - Tree Indexes: B+Trees (CMU Intro to Database Systems)

CMU Database Group · 1:22:14

Lecture 8 of CMU 15-445/645 (Fall 2024) is a full treatment of the B+Tree, the data structure behind virtually every CREATE INDEX in a real database system. It starts by separating indexes (find where a key is) from filters (guess whether a key exists), walks through the history of the B-Tree family — Bayer &...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#09 - Vector Indexes, Inverted Indexes, Filters, Tries ✸ TiDB Talk (CMU Intro to Database Systems)

CMU Database Group · 1:21:10

Lecture 9 of CMU 15-445/645 (Fall 2024) is deliberately a brain dump of the index and filter data structures a database engineer should know beyond the B+Tree 0:27. Andy Pavlo opens by separating filters (does this key exist?) from indexes (it exists, and here is where) 2:34, then walks through Bloom filters and...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#10 - Index Concurrency Control (CMU Intro to Database Systems)

CMU Database Group · 1:16:42

A university lecture (CMU 15-445/645, Fall 2024) that drops the single-threaded assumption made in all previous index lectures and shows how to make index data structures safe under concurrent access. It starts from first principles — locks vs latches, latch modes, and how latches are actually implemented on top of...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#11 - Sorting & Aggregation Algorithms ✸ dbt Database Talk (CMU Intro to Database Systems)

CMU Database Group · 1:17:56

Lecture 11 of CMU 15-445/645 (Fall 2024) moves up the stack from storage and indexes into query execution, covering the operator algorithms a DBMS uses when intermediate results are too large to fit in memory. Andy Pavlo works through top-N heap sort, external merge sort (its two-way form, its generalized B-way...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#12 - Join Algorithms: Hash, Sort-Merge, Nested Loop Joins (CMU Intro to Database Systems)

CMU Database Group · 1:14:22

Andy Pavlo walks through how a DBMS physically executes a join, restricting the discussion to inner equi-joins between two tables and using number of disk I/Os as the single cost metric. He builds up from the naive nested loop join (50 million I/Os, 1.3 hours on the running example) through block and index nested...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#13 - Query Execution Part 1 (CMU Intro to Database Systems)

CMU Database Group · 1:23:19

> CMU Database Group · 1:23:19 · Watch on YouTube > Type: university lecture / educational video (CMU 15-445/645, Fall 2024)Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#14 - Query Execution Part 2 ✸ ClickHouse Database Talk (CMU Intro to Database Systems)

CMU Database Group · 1:02:49

The lecture covers how a DBMS executes queries in parallel: how workers are organized (process per worker, thread per worker, embedded), how a single query is split across them, and how disk I/O is parallelized. It builds up from inter-query parallelism to intra-query parallelism — intra-operator (horizontal),...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#15 - Query Planning & Optimization (CMU Intro to Database Systems)

CMU Database Group · 1:21:18

Andy Pavlo's CMU 15-445/645 lecture on how a database system turns a declarative SQL string into an executable physical plan. It opens with a motivating example that drives one query from ~2,000,000 I/Os down to 37 by successively replacing a cartesian product, swapping join algorithms, enabling pipelining, and...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#16 - Concurrency Control Theory ✸ Firebolt Database Talk (CMU Intro to Database Systems)

CMU Database Group · 1:27:09

A university lecture (CMU 15-445/645, Fall 2024) that opens the transactions block of the course. Andy Pavlo motivates concurrency control with a bank-account example showing how a crash mid-transaction and two concurrent withdrawals both corrupt the database, then dismantles the two naive fixes — running one...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#17 - Two-Phase Locking Concurrency Control (CMU Intro to Database Systems)

CMU Database Group · 1:05:22

This lecture (CMU 15-445/645, Fall 2024) moves from the previous class's static schedules — where every read and write is known in advance — to dynamic schedules, where the DBMS must decide on the fly which transaction may touch which object. The solution presented is two-phase locking (2PL): transactions acquire...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#18 - Optimistic Concurrency Control ✸ Weaviate Database Talk (CMU Intro to Database Systems)

CMU Database Group · 1:20:53

Lecture 18 of CMU 15-445/645 (Fall 2024) covers Optimistic Concurrency Control (OCC), the counterpart to the pessimistic two-phase locking protocol from the previous class. Andy Pavlo builds up the timestamp-ordering machinery OCC rests on, walks through its three phases (read into a private workspace, validate,...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#19 - Multi-Version Concurrency Control (CMU Intro to Database Systems)

CMU Database Group · 1:27:07

Andy Pavlo's lecture 19 of CMU 15-445/645 (Fall 2024) explains Multi-Version Concurrency Control (MVCC): the technique of keeping multiple physical versions of a single logical tuple so that writers never block readers and readers never block writers. The lecture walks through the visibility mechanics (BEGIN/END...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#20 - Database Logging ✸ Confluent Database Talk (CMU Intro to Database Systems)

CMU Database Group · 1:19:21

Lecture 20 of CMU 15-445/645 (Fall 2024) covers the first half of database recovery: everything a DBMS must do while transactions are running so that it can survive a crash later. Andy Pavlo starts from the durability gap left by concurrency control, derives the two buffer pool policies (STEAL and FORCE) that...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#21 - Database Recovery with ARIES (CMU Intro to Database Systems)

CMU Database Group · 1:12:55

University lecture (CMU 15-445/645, Fall 2024) on ARIES, the canonical crash-recovery protocol for disk-oriented database systems. Building on the previous lecture's write-ahead log, it explains how a DBMS running under a STEAL + NO-FORCE buffer pool policy restarts after an unclean shutdown and restores atomicity,...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#22 - Distributed Database Architectures ✸ DataStax Database Talk (CMU Intro to Database Systems)

CMU Database Group · 1:23:02

A guest lecture in CMU 15-445/645 (Fall 2024) that makes the jump from the single-node DBMS students have been building all semester to distributed database systems, framing every new difficulty as a coordination problem. It walks the classic four-way architecture classification (shared everything / nothing / disk...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#23 - Distributed Transactional Databases (CMU Intro to Database Systems)

CMU Database Group · 1:24:53

Lecture 23 of CMU 15-445/645 (Fall 2024) covers how an OLTP database keeps ACID guarantees when its data is spread across multiple nodes. It walks the full design space of replication — primary-replica vs multi-primary, K-safety, synchronous/quorum/eventual propagation, continuous vs on-commit timing, and...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#24 - Distributed Analytical Databases (CMU Intro to Database Systems)

CMU Database Group · 1:22:55

The final lecture of CMU 15-445/645 (Fall 2024) covers how an OLAP database system changes when it must run across many nodes. It starts with the environment analytics lives in — OLTP silos feeding a warehouse via ETL/ELT, and the star/snowflake schemas warehouses use — then walks through the distributed execution...Not startedEnglishDatabasesCourses

CMU Intro to Database Systems (15-445/645 - Fall 2024)

#25 - BigQuery + Snowflake + Redshift + Databricks + DuckDB (CMU Intro to Database Systems)

CMU Database Group · 1:25:57

The final lecture of CMU 15-445/645 (Fall 2024) opens with course logistics and a rapid review of every exam topic since the midterm, then spends the bulk of its time on how modern analytical (OLAP) database systems actually get their speed. Andy Pavlo first establishes the two foundational techniques — writing...Not startedEnglishDatabasesCourses

DDIA, cloud tradeoffs, formal verification, and local-first software.Not startedEnglishDatabasesDistributed systems

Designing Data-intensive Applications with Martin Kleppmann

The Pragmatic Engineer · 1:25:49

Interview formats, preparation, and explaining your reasoning.Not startedSpanishCareersInterviews

EL ERROR que TE DESCARTA en una Entrevista Técnica

Yari Taft · 20:10

A GitHub outage and the engineering behind the failure.Not startedSpanishDatabasesDistributed systems

El error que tumbó a GitHub, explicado

BettaTech · 17:28

Business models, Toyota, entrepreneurship, and finding work. Episode 150.Not startedSpanishBusinessTechnology

El NEGOCIO de la MUERTE, Método TOYOTA y cómo CONSEGUIR TRABAJO sin CV #150

spicy4tuna · 2:10:10

Bitcoin, business, economics, and current affairs. Episode 149.Not startedSpanishBusinessTechnology

"Hackean" BITCOIN, ESPAÑA es un ESTADO FALLIDO y el NEGOCIO de la TERCERA EDAD #149

spicy4tuna · 2:01:42

Connection pooling, sharding, IDs, and Postgres at scale.Not startedEnglishDatabasesDistributed systems

How Instagram Scaled Postgres to 2 Billion Users

Akhil Sharma · 22:37

A Go application benchmark comparing monoliths and microservices under equal hardware budgets, with HTTP, gRPC, resource rebalancing, and organizational tradeoffs.Not startedEnglishArchitectureDistributed systemsSystem designCloudDatabases

How much slower are Microservices? (I tested)

Arjay McCandless · 12:49

Architecture decisions and system design reasoning.Not startedEnglishSystem designCloud

How Senior Engineers Actually Think About System Design & Architecture | Full Course

JavaScript Mastery · 38:00

Retrieval, indexing, and architecture for RAG applications.Not startedEnglishAI modelsArchitecture

How to Build a Scalable RAG System for AI Apps (Full Architecture)

ByteMonk · 15:52

Claude usage limits, costs, and coding workflows.Not startedEnglishAI codingAgent workflows

How To Give Claude Unlimited Usage

Theo - t3․gg · 38:47

Katie Dill explains how to preserve design intent and quality with AI through explicit standards, opinionated tools, editing, and creative exploration.Not startedEnglishAI codingAgent workflowsDesign

How to scale intent, quality, and artistry with Al | Katie Dill (Stripe)

Lenny's Podcast · 21:48

Subscription economics, parallel agents, verification, and overnight workflows.Not startedEnglishAI codingAgent workflows

If you have a Claude sub, watch this

Theo - t3․gg · 1:06:36

Kimi K3 benchmarks, pricing, and practical tests.Not startedSpanishAI modelsArchitecture

Kimi K3 es Salvaje (lo siento, Claude)

midudev · 30:15

A stateful agent skill for guided learning.Not startedEnglishAI codingAgent workflows

Learn anything with the /teach skill

Matt Pocock · 13:04

Load testing and handling high request throughput.Not startedEnglishSystem designCloud

Let's Handle 1 Million Requests per Second, It's Scarier Than You Think!

Cododev · 2:39:18

pstack and engineering workflows at SpaceX.Not startedEnglishAI codingAgent workflows

LIVE: Poteto (creator of pstack) on shipping 1,000's of PR's a month at SpaceX

Matt Pocock · 1:05:36

Welcome to the LLM evaluation course

Ninety-second welcome video for Evidently AI's course on LLM evaluations, presented by instructor Elena. It positions the course as a high-level, no-coding introduction for anyone building (or considering building) an LLM-powered product, and walks through the full curriculum: from LLM fundamentals and benchmarks,...Not startedEnglishLLM evaluationCourses

Evidently AI · 1:31

What is an LLM-powered product?

Short educational explainer that sets the ground for an LLM evaluation course: before evaluating anything, it defines what is being evaluated. It covers what an LLM is and how you interact with it, what makes software an "LLM-powered product" (from single-prompt features to RAG systems and agents), and closes with...Not startedEnglishLLM evaluationCourses

Evidently AI · 3:07

LLM evaluation benchmarks

> Evidently AI · 3:06 · Watch on YouTubeNot startedEnglishLLM evaluationCourses

Evidently AI · 3:06

How to evaluate an LLM application

A big-picture introduction to evaluating LLM-powered applications, focused on the pre-deployment phase. It explains why LLM testing differs from traditional software testing (non-determinism), frames quality as capabilities plus risks, and walks through the maturity path from informal vibe checks to manual labeling...Not startedEnglishLLM evaluationCourses

Evidently AI · 5:59

LLM evaluation datasets: test cases and synthetic data

An educational video on building evaluation datasets for LLM applications. It covers five sources of evaluation data (manual test cases, existing data, beta users, public benchmarks, and synthetic data), three ways to use LLM-generated synthetic data (plausible inputs, RAG ground truth, and input diversification),...Not startedEnglishLLM evaluationCourses

Evidently AI · 6:06

LLM evaluation methods and metrics

An educational overview of the main automated methods for evaluating LLM outputs. After stressing that manual review with domain experts always comes first, it splits automated methods into ground truth-based and open-ended groups, then walks through each technique: predictive metrics (accuracy/precision/recall),...Not startedEnglishLLM evaluationCourses

Evidently AI · 5:09

LLM-as-a-judge: evaluating LLMs with LLMs

Educational explainer on LLM-as-a-judge: using an LLM to evaluate the outputs of another LLM. It explains why the approach is trustworthy despite sounding circular (critiquing is easier than creating; the judge has one narrow job), walks through the main judge types (pairwise comparison, direct scoring, direct...Not startedEnglishLLM evaluationCourses

Evidently AI · 5:41

How to run LLM evals with no code | PRACTICE

A hands-on tutorial showing how to run LLM evaluations entirely through the Evidently Cloud UI, with no code. It walks through generating synthetic test data (plausible inputs from a task description, and ground-truth Q&A pairs from a source document for RAG), uploading a Q&A dataset and evaluating it with a mix of...Not startedEnglishLLM evaluationCourses

Evidently AI · 12:27

LLM safety and red-teaming

A short educational video on LLM safety for application builders. It walks through four things that can go wrong with LLM apps — off-topic use, hallucinations, jailbreaks, and data leaks — each illustrated with a real-world incident (Klarna, Air Canada, Chevrolet, DPD). It then presents a defense strategy: start...Not startedEnglishLLM evaluationCourses

Evidently AI · 5:11

LLM observability in production: tracing and online evals

Educational video on evaluating LLM applications after they ship. It covers what you can track in production (product metrics, manual log review, software monitoring, and AI quality monitoring), draws the line between monitoring and observability, and then walks through the three-step production observability...Not startedEnglishLLM evaluationCourses

Evidently AI · 5:08

AI agent and RAG evaluation

Educational explainer on how to evaluate complex AI systems — RAG pipelines, chatbots, and AI agents — that go beyond the simple input/output shape of tasks like summarization. It defines each system type, then develops three general evaluation strategies: splitting the system into smaller testable components,...Not startedEnglishLLM evaluationCourses

Evidently AI · 6:04

A business case for LLM evaluations

> Evidently AI · 4:05 · Watch on YouTubeNot startedEnglishLLM evaluationCourses

Evidently AI · 4:05

How to continuously improve LLM products?

Final video of the Evidently AI LLM evaluation course (2:33). It recaps the two kinds of evals covered in the course — evaluating LLM models and evaluating LLM systems built on them — and connects everything into a single end-to-end workflow: evaluation datasets → experimental iteration → deployment with guardrails...Not startedEnglishLLM evaluationCourses

Evidently AI · 2:33

Matt Pocock on communicating intent to coding agents, improving their working environment, and earning trust through verifiable work.Not startedEnglishAI codingAgent workflowsCareersInterviews

Matt Pocock: The Most Valuable Skill to Learn in the Age of AI

Nate Herk | AI Automation · 44:50

Theo explains AI harnesses, T3 Code's MCP architecture, skill portability, and why he expects harness choice to matter less.Not startedEnglishAI codingAgent workflowsArchitecture

My last video about ai harnesses

Theo - t3․gg · 49:29

Practical architecture without premature scaling.Not startedSpanishSystem designCloud

No sos Netflix. Cuando tu sistema no necesita escalar a un millón de usuarios. - J. Rodríguez Monti

Nerdearla · 27:47

Theo compares OpenAI and Claude subscription limits, task costs, and code-review quality after OpenAI's usage increase.Not startedEnglishAI codingAI modelsLLM evaluationAgent workflows

OpenAI is getting desperate

Theo - t3․gg · 15:50

The value of framework expertise as coding agents improve.Not startedEnglishCareersInterviews

should you learn .NET & C# in 2026

Amichai Mantinband · 15:34

A hands-on review of Matt Pocock's skills and pstack.Not startedEnglishAI codingAgent workflows

So I tried Matt's skills...

Theo - t3․gg · 38:21

Hands-on model evaluation, demos, and code audits.Not startedEnglishAI modelsArchitecture

So I've been testing Gemini 4...

Theo - t3․gg · 38:30

How AI changes engineering roles and the skills to develop.Not startedEnglishCareersInterviews

Stanford AI Expert: These 3 Jobs Will EXPLODE in the Next 5 Years!

Sajjaad Khader · 13:50

How persistent agents combine durable workflows, cloud computers, tool discovery, context management, memory, and product evaluation.Not startedEnglishAgent workflowsArchitectureDistributed systems

Stanford CS146S: How always-on agents work

leerob · 45:17

Coding interviews, engineering judgment, and career decisions.Not startedEnglishCareersInterviews

Tech interviews with NeetCode

The Pragmatic Engineer · 1:29:56

Learning from experts, sharing work, and automating repetitive tasks.Not startedEnglishCareersInterviews

The Art of Winning in Tech

Sajjaad Khader · 11:30

Message storage, Cassandra bottlenecks, and migration to ScyllaDB.Not startedEnglishDatabasesDistributed systems

The Real Reason Discord Left Cassandra

ByteMonk · 19:40

Developer burnout, motivation, and boundaries around AI coding.Not startedEnglishAI codingAgent workflows

The True Cost of AI Coding

Syntax · 24:27

Big Tech careers, interviews, English, and international opportunities.Not startedSpanishCareersInterviews

Trabajó en Google, Facebook y YouTube: Hablando con Ingeniero de Silicon Valley 🔴

diegoveloper · 2:18:40

Choosing databases around access patterns.Not startedEnglishDatabasesDistributed systems

Why Netflix, Instagram, and Twitter Pick Different Databases

ByteMonk · 10:49

Prompt-driven diagnostics, delegation, and connected workflows.Not startedEnglishAI codingAgent workflows

Your prompts kinda suck

Theo - t3․gg · 31:47