Who it’s for · ENGINEER
Application engineers
What other teams hit in production, and the parts you can copy outright. Here is what’s directly relevant to you across the three conferences.
100relevant756min must-watch3conferences
Conference
Scenario
Topic
Showing 100 of 100 · orange dot = unread
- A ready-to-use four-part checklist for reviewing skills—trigger, structure, steering, pruning—to help you get out of Skill Hell.AI Engineer World's FairFor · Skill authors and reviewers / Agent tuning engineersAgentContext1 min on screen21 min totalWorks as a podcast
- Five minutes on an edge case no RAG tutorial covers: what to do when all of your documents are relevant and the whole dataset gets replaced constantly.Luis Romero-Sevilla · AI Engineer World's FairFor · Engineers choosing a RAG architecture / Teams shipping GraphRAGContext1 min on screen6 min totalPart listen, part watch
- It's not that the model is bad — the agent has no eyes: a practical checklist for building it verification toolsJohan Lajili · AI Engineer World's FairFor · AI coders working on a brownfield codebase / Engineering leadsAgentAI CodingEvals2 min on screen10 min totalPart listen, part watch
- Turn production logs into replayable test beds, so every fix is proven to help and proven to break nothing that already workedSoheil Feizi · AI Engineer World's FairFor · Agent engineers firefighting after launch / Algorithm and platform leads working on agent optimizationAgentEvalsContext2 min on screen23 min totalWorks as a podcast
- Frontline view from Meta: agents don't fail on intelligence, they fail on infrastructureNishant Gupta · AI Engineer World's FairFor · Agent platform architects / Infrastructure engineersAgentContextAI Product2 min on screen7 min totalPart listen, part watch
- Measured, not guessed: 90% of your AI coding bill is context that was not relevant. One local search layer cuts 94% of it.Rajkumar Sakthivel · AI Engineer World's FairFor · Engineers paying their own bill / Team tech leadsAI CodingContext2 min on screen11 min totalPart listen, part watch
- A view from inside Meta: agent evaluation isn't benchmark chasing, it's production engineeringNishant Gupta · AI Engineer World's FairFor · Agent platform lead / Engineering manager shipping agentsAgentEvals2 min on screen8 min totalPart listen, part watch
- Uses Cursor's measured numbers to puncture "RAG is dead" and spell out what retrieval has actually becomeKuba Rogut · AI Engineer World's FairFor · Engineers building code base retrieval / Technical decision-makers weighing whether to indexAgentContextAI Coding2 min on screen11 min totalPart listen, part watch
- After 500,000 sensor names confused the LLM, a tree-structured rebuild won back 100% accuracy and a 300x cost cutAI Engineer World's FairFor · LLM application architect / Agent cost ownerAgentContextEvalsAI Product3 min on screen16 min totalPart listen, part watch
- 12 minutes on the three layers of infrastructure the internet of agents is missing, and how MIT fills them with an open index and a sandbox you can actually runRamesh Raskar · AI Engineer World's FairFor · Agent platform and protocol developers / Multi-agent systems researchersAgent3 min on screen12 min totalPart listen, part watch
- Break "done" out of a single green checkmark into a verifiable object, or your agents will produce slop at scaleDotta · AI Engineer World's FairFor · AI engineering lead / Platform architectAgentEvals3 min on screen7 min totalPart listen, part watch
- A 100-person factory grew a 36-agent brain with zero GPUs, for a fraction of the agency's quoteRushabh Doshi · AI Engineer World's FairFor · Owner of a small or mid-sized manufacturer / Successor in a family businessAgentContextAI Product3 min on screen10 min totalPart listen, part watch
- Notion's Geoffrey Litt reframes "do we still need to read code in the AI era" as a question of participation, and gives you fixes you can use today.Geoffrey Litt · AI Engineer World's FairFor · Engineers who lean heavily on agents / Tech leadsAgentAI Coding3 min on screen20 min totalPart listen, part watch
- 9 minutes on why "can you verify" is replacing "can you code": a hands-on retrospective of building Vector Harness.Talha Sheikh · AI Engineer World's FairFor · AI coding engineers / AI tooling leadsAgentAI CodingEvals3 min on screen10 min totalPart listen, part watch
- An agent fleet across three machines: five things that broke, and an honest list of what's still unsolvedKyle Jaejun Lee · AI Engineer World's FairFor · Engineers running multiple agents / People building agent frameworksAgentAI CodingContext3 min on screen9 min totalPart listen, part watch
- Turns backdoor detection into a build-time unit test costing one forward pass, and admits recall is only a quarterSachin Kumar · AI Engineer World's FairFor · Model safety lead / ML platform engineerEvals3 min on screen14 min totalPart listen, part watch
- An ablation that undercuts its own pitch: self-healing ETL reliability comes from structure, not RLAnna Marie Benzon · AI Engineer World's FairFor · Data platform engineers / Tech leadsAgentEvals3 min on screen15 min totalPart listen, part watch
- Validated on 3M real records: compliance risk lives between the documentsVarsha Shah · AI Engineer World's FairFor · Risk and fraud-detection tech leads / Architects of cross-border financial complianceAI ProductEvals3 min on screen19 min totalPart listen, part watch
- In five minutes, see the five leaks that quietly burn money in production agents — and the code to stop each oneErik Hanchett · AI Engineer World's FairFor · Agent backend developers / Anyone bleeding on their token billAgentContext3 min on screen6 min totalNeeds your eyes
- How Block used 50 Champions to grow automated PRs 21x — the complete scaling roadmapAngie Jones · AI Engineer World's FairFor · Engineering effectiveness leads / Platform/DevEx engineersAgentAI CodingContext3 min on screen18 min totalPart listen, part watch
- The full spec-driven development flow, tool-agnostic: requirements, design and tasks documents before any code is written, to keep a wandering AI assistant on the railsErik Hanchett · AI Engineer World's FairFor · Engineers already using coding assistants / Tech leadsAI CodingContextEvals3 min on screen18 min totalPart listen, part watch
- Four minutes of live runs: giving the agent better "eyes" beats giving it a better modelKushan Raj · AI Engineer World's FairFor · Browser agent developers / Product leads for agent toolingAgentContext3 min on screen4 min totalNeeds your eyes
- Reclassify the log from system exhaust to the agent itself, and reliability, scale and lock-in all come loose at onceIshaan Sehgal · AI Engineer World's FairFor · Runtime developers / Platform decision-makersAgentContext3 min on screen15 min totalPart listen, part watch
- "I did a search" is often a lie — a live GPT-5 run fails all five sites, then lands all fiveRafael Levi · AI Engineer World's FairFor · Developers wiring web access into agents / Product leads dealing with dead citationsAgentContextAI Product3 min on screen16 min totalPart listen, part watch
- Don't put the repo into context — let the model write code to inspect it and recursively call sub-models; the open source RLM implementation, demoed live end to endShashi · AI Engineer World's FairFor · Coding agent engineers / Developers who want to reproduce RLMAgentAI CodingContext4 min on screen17 min totalPart listen, part watch
- Don't change your terminal workflow — put four parallel coding agents on your phone exactly as they areConnor Adams · AI Engineer World's FairFor · Terminal-based multi-agent developers / Anyone who wants to check on progress from their phoneAgentAI Coding4 min on screen9 min totalNeeds your eyes
- Recognize the worse version of CI/CD you're rebuilding by hand, and stop it with five gatesSumaiya Shrabony · AI Engineer World's FairFor · Solo agent builders / Content automation authorsAgentEvals4 min on screen11 min totalPart listen, part watch
- The talk is itself an AI game: runtime decision-making running live, and an NPC match that plays out differently every timeDavid Hoe · AI Engineer World's FairFor · Indie AI game developers / Content platform product leadsAI ProductAgentAI Coding4 min on screen18 min totalPart listen, part watch
- Replacing 15 tools with a single REPL: the full post-mortem of taking a spreadsheet agent from 50% to 92%Nuno Campos · AI Engineer World's FairFor · People designing agent tool interfaces / People who own an agent evaluation systemAgentAI CodingEvalsContext4 min on screen19 min totalPart listen, part watch
- Watch AI run a chess-commentary YouTube channel entirely on its own: the engine can play, the LLM can talk, and combining them is the holy grail.Stephan Steinfurt · AI Engineer World's FairFor · LLM agent engineers / AI content foundersAgentAI Product4 min on screen17 min totalPart listen, part watch
- Once your agent ships, how do you find problems, send PRs, and gate them? Wandero's production practice: a half-hour loop.Raphael Kalandadze · AI Engineer World's FairFor · Engineering leads on agent products / Developers with an agent already in productionAgentEvalsAI Product4 min on screen20 min totalPart listen, part watch
- Can't reproduce that production agent failure? Stop fighting for determinism — record and replay turns it into a free regression test.Tisha Chawla · AI Engineer World's FairFor · Production agent engineers / AI testing leadsAgentEvals4 min on screen14 min totalPart listen, part watch
- Around the 200ms tyranny of latency: three engineering rules for real-time voice in, visuals out agentsAllen Pike · AI Engineer World's FairFor · Voice agent builders / Real-time AI product leadsAI ProductAgentContext4 min on screen13 min totalPart listen, part watch
- Three levers for getting research into production: a handoff doc, a repo skeleton, and stacked-diff decompositionVaidas Razgaitis · AI Engineer World's FairFor · Tech leads of mixed teams / ML researchersAI ProductAI Coding4 min on screen15 min totalPart listen, part watch
- Let anyone ask business questions in natural language, then freeze the answer into a widget with zero ongoing LLM costGarrett Galow · AI Engineer World's FairFor · Data and analytics teams / AI agent developersAgentContextEvalsAI Product4 min on screen19 min totalPart listen, part watch
- How PostHog refines trillions of noisy signals into green PRs an engineer can merge on waking upJoshua Snyder · AI Engineer World's FairFor · Platform and infrastructure engineers / AI pipeline leadsAgentAI CodingEvalsAI Product4 min on screen16 min totalPart listen, part watch
- Compress a full KV cache into "weights" in one forward pass, filling the intermediate memory layer that sits between lossless cache and fine-tuning.Cursor CompileFor · Inference optimization researcher / Agent memory researcherAgentContext4 min on screen13 min totalPart listen, part watch
- Two years of GitHub data, one claim: the AI application layer is changing its name to TypeScript.Roberto Stagi · AI Engineer World's FairFor · Whoever owns the agent stack decision / Full-stack application engineersAI CodingAgent5 min on screen14 min totalPart listen, part watch
- Data from 22,000 engineers ends the "should we still read AI code" fight: whether you read is routed by the risk of the change.Alex Volkov · AI Engineer World's FairFor · Engineers leaning hard on agents / Tech leads setting review standardsAgentAI CodingEvals5 min on screen22 min totalPart listen, part watch
- The OpenAI Codex team breaks it down: from watching ten terminal windows to talking to one long-running manager agent.Romain Huet · AI Engineer World's FairFor · Engineers working many things in parallel / Engineering team leadsAgentAI CodingAI ProductContext5 min on screen25 min totalPart listen, part watch
- Takes "one version for everyone" apart as a cost calculation, then hands you the architecture and verification problems of a version per user.Iris ten Teije · AI Engineer World's FairFor · Horizontal SaaS product architects / CI and release system ownersAgentAI CodingAI ProductEvals5 min on screen20 min totalPart listen, part watch
- A designer who doesn't ship code, on how a 30-day experiment with 500 people turned her into someone who ships productsSanja Grbic · AI Engineer World's FairFor · Designers who don't write code / Team leadsAI CodingDesign-to-CodeContextAI Product5 min on screen18 min totalPart listen, part watch
- Watch a company actually make "the specification is the product, the implementation is generated" work, instead of stopping at the slogan.Dominik Tornow · AI Engineer World's FairFor · Distributed systems engineers / Platform/infrastructure foundersAgentAI Coding5 min on screen18 min totalPart listen, part watch
- Don't blame the model for bad graphics. Change the medium: HTML is the agent's native language for visuals.Amol Kapoor · AI Engineer World's FairFor · AI presentation product leads / Engineers wiring tools to agentsAgentAI CodingDesign-to-CodeAI Product5 min on screen7 min totalNeeds your eyes
- Don't let eval signal die in the dashboard — feed it back as retrieval weight, with benchmarks and a live demoSonam Pankaj · AI Engineer World's FairFor · Agent memory / RAG engineers / Developers stuck with agents that keep failing the same wayAgentEvalsContext5 min on screen16 min totalPart listen, part watch
- Accuracy falls to 13.6% at 741 tools: measured numbers on how tools should be selectedSohail Shaikh · AI Engineer World's FairFor · Agent engineers / AI platform architectsAgentContextEvals5 min on screen28 min totalPart listen, part watch
- A booking failure that forced out a four-layer prompt architecture: turning what the brand must never say into a hard rule.Isadora Martin-Dye · AI Engineer World's FairFor · LLM product leads / Conversational AI engineersContextAI ProductAgent5 min on screen21 min totalPart listen, part watch
- Entropy-reduction physics explains why token maxing keeps costing more for less: context is the other half of efficiency the whole industry skipped.Ben Geist · Cursor CompileFor · Agent systems engineers / Inference efficiency researchersContextAgent5 min on screen15 min totalPart listen, part watch
- One brief Slack message — "fix this thing" — and OpenClaw already knows what you mean, with agents writing the code in parallel.Jeffrey Lee-Chan · AI Engineer World's FairFor · Experienced AI coding tool users / Platform / DevEx engineersAgentAI CodingContext6 min on screen15 min totalPart listen, part watch
- As models keep getting more powerful, the harness you fix ahead of runtime becomes the bottleneck — let it emerge instead.Rajiv Chandegra · AI Engineer World's FairFor · Multi-agent systems engineers / AI architectsAgentAI Coding6 min on screen37 min totalPart listen, part watch
- Same model, only the search tool swapped, and it nearly hits the ceiling - the bottleneck is retrieval, not reasoningAmir · AI Engineer World's FairFor · RAG / search agent engineers / People writing agent harnessesAgentEvalsContext6 min on screen14 min totalNeeds your eyes
- Carbon accounting has no single right answer, so he moved validation off the answer and onto the process.Andrew Dumit · AI Engineer World's FairFor · Agent platform leads / Product leads in domains with no answer keyAgentAI CodingEvalsContext6 min on screen17 min totalPart listen, part watch
- Three months hand-building a pocket AI terminal, from blown-up boards to a working RPGLech Kalinowski · AI Engineer World's FairFor · AI hardware makers / Embedded firmware engineersAI ProductAgentContext6 min on screen25 min totalPart listen, part watch
- Turns quantization, caching, and distillation for diffusion inference into a roadmap you can start on todayZiv Ilan · AI Engineer World's FairFor · Inference deployment engineers / Generative product leadsAI Product6 min on screen19 min totalPart listen, part watch
- 500 美元、21 小时 RL 训练,4B 模型工具调用打赢 235BKobie Crawford · AI Engineer World's FairFor · Agent developers / Enterprise tech leadsAgentEvals6 min on screen21 min totalPart listen, part watch
- Designers and product owners delivering code: a complete open-source practice for two-way Figma-and-code syncJustin Meyer · Figma ConfigFor · Frontend lead / Design system maintainerAgentDesign-to-CodeAI CodingContext6 min on screen20 min totalPart listen, part watch
- Letting agents loose on a 600TB production database doesn't run on trust — it runs on infrastructure primitives.Sam Lambert · Cursor CompileFor · Platform and infrastructure engineers / Database ownersAgentAI ProductContextAI Coding6 min on screen26 min totalPart listen, part watch
- Uses a neural network to invent 1,024 new human-readable symbols from scratch — arguing that notation itself is part of intelligence.Linus Lee · Cursor CompileFor · AI interface designers / Representation-learning researchersAI Product6 min on screen17 min totalPart listen, part watch
- A Microsoft engineer's four-part guardrail kit: with guardrails you're a 20x engineer, without them you're 20x the slop.Chris Noring · AI Engineer World's FairFor · Developers doing AI-assisted coding / Tech leadsAgentAI CodingContext7 min on screen23 min totalPart listen, part watch
- On Fable's launch day, an Anthropic member on why what contains the models is usThariq Shihipar · AI Engineer World's FairFor · Engineers who write prompts / Heavy Claude Code usersAI CodingAgentContextAI Product7 min on screen19 min totalPart listen, part watch
- A rare enterprise production record: a self-built agent loop, an A2A contract, sandboxing and humans in the loop, end to endGabe de Mesa · AI Engineer World's FairFor · Agent platform architect / AI application backend engineerAgentEvalsContextAI Product7 min on screen19 min totalPart listen, part watch
- Coding agents aren't short on intelligence, they're short on reliability. Recursive decomposition turns the lucky golden session into a repeatable result.Raymond Weitekamp · AI Engineer World's FairFor · Heavy coding agent users / AI agent buildersAgentAI CodingEvalsContext7 min on screen24 min totalPart listen, part watch
- Design agentic systems with the engineering discipline you already have — method you can copy, no trend talk.Angie Jones · AI Engineer World's FairFor · Agentic systems engineer / Tech leadAgentAI CodingContext7 min on screen20 min totalPart listen, part watch
- How an $85K failed banking chatbot shipped in 8 weeks — with the model picked in week 7Sandipan Bhaumik · AI Engineer World's FairFor · AI platform engineering lead / Data platform leadAgentEvalsAI Product7 min on screen37 min totalPart listen, part watch
- When agents scale infinitely, the bottleneck becomes your attention — a working developer's flow for not getting friedZack Proser · AI Engineer World's FairFor · Developers running agents in parallel / Engineering leadsAgentAI CodingContext7 min on screen25 min totalPart listen, part watch
- No Docker rebuild: add a decorator to a Python function and throw the code onto a GPU cloud with hot reload, right from your local IDEAudry Hsu · AI Engineer World's FairFor · Developers self-hosting models / Developers orchestrating multiple modelsAI CodingAI Product7 min on screen20 min totalPart listen, part watch
- Notion had no design system until 2025: the year-long rebuild, and how they taught the agents table mannersTamara · Figma ConfigFor · Design system leads / Front-end platform engineersAI CodingAgentDesign-to-Code7 min on screen21 min totalPart listen, part watch
- Let the AI audit its own design work: two months of build and QA down to two hoursMike Green · Figma ConfigFor · Design system leads / Front-end team leadsDesign-to-CodeAgentAI Coding7 min on screen20 min totalPart listen, part watch
- Hand the whole agent iteration loop over to agents; the eval gate is the only termination condition.Benedikt Sanftl · AI Engineer World's FairFor · Production agent engineers / AI tech leadsAgentEvalsAI Coding8 min on screen35 min totalPart listen, part watch
- An open source library that turns PDFs into structure an LLM can actually understand — and lets you drop the vector databaseCedric Clyburn · AI Engineer World's FairFor · RAG engineers / Teams running everything in-houseContextAgent8 min on screen21 min totalPart listen, part watch
- From one odd nesting in ChatGPT's DOM to the full set of trade-offs behind isolating third-party UIFrédéric Barthelet · AI Engineer World's FairFor · MCP app developers / App submitters stuck in reviewAgentAI Product8 min on screen20 min totalNeeds your eyes
- Top-ten on the open leaderboard from a single GPU: DeepMind on when self-hosting Gemma 4 pays off, with a live demo.Gus Martins · AI Engineer World's FairFor · Leads evaluating self-hosting / Enterprise architects and legalAgentAI CodingEvalsAI Product8 min on screen21 min totalPart listen, part watch
- 18 minutes from an empty file to an ACP agent that reads and writes files and opens a terminalBennet Fenner · AI Engineer World's FairFor · Agent authors who want to plug into an editor / Technical decision-makers evaluating ACPAgentAI Coding9 min on screen18 min totalNeeds your eyes
- An hour on every MCP Apps primitive and how to get into the three big stores, ending on the claim that MCP is the new websitePietro Zullo · AI Engineer World's FairFor · MCP server developers / AI product foundersAgentAI Product9 min on screen29 min totalPart listen, part watch
- One metaphor, the amnesiac genius, explains the agent's multi-repo and memory problem — then a live demo fixes it without changing a line of code in any repoVictor Savkin · AI Engineer World's FairFor · Platform engineers / Tech leadsAgentAI CodingContext9 min on screen20 min totalNeeds your eyes
- One claims review case, walked end to end through the four steps from requirements to productionApoorva Joshi · AI Engineer World's FairFor · AI application developers / Tech leadsAI ProductAgentEvalsAI Coding10 min on screen29 min totalPart listen, part watch
- A Google engineer breaks down four levels of generating interfaces with AI at runtime — as candid about what broke as about the demosCraig Labenz · Figma ConfigFor · Front-end engineers / Product leadsAgentAI Product10 min on screen20 min totalNeeds your eyes
- Boston Dynamics from the inside: how generally capable hardware turns robotics into a software problemMegan · Figma ConfigFor · Software engineers on AI/agent products / AI product designersAgentAI ProductEvals10 min on screen21 min totalNeeds your eyes
- Turning "generate one image" into a creative pipeline you can hand off — real client workflows pulled apart on screenJenny Shi · Figma ConfigFor · Brand-side creative lead / Anyone building AI creative workflowsAI ProductContext11 min on screen21 min totalNeeds your eyes
- Film a real sword swing or a drop, and turn it into a reusable easing curve in Figma on the spotPatrick Flaherty · Figma ConfigFor · UI and motion designers / Design system maintainersDesign-to-Code11 min on screen22 min totalNeeds your eyes
- Govern product copy like a design system, with one system spanning Figma, code, and pull requestsJessica · Figma ConfigFor · Design system leads / Frontend and engineering leadsAI ProductAgentContextAI Coding11 min on screen20 min totalNeeds your eyes
- Expose your local agent safely, then change code from your phone and watch the UI updateNick Taylor · AI Engineer World's FairFor · Self-hosted agent developers / MCP tool developersAgentAI Coding12 min on screen17 min totalNeeds your eyes
- Swapping cloud Sonnet for on-device Llama 3.2 without losing performance: a right-sizing eval you can actually copyRachel Lee Nabors · AI Engineer World's FairFor · LLM application engineers / AI product leadsEvalsAI Product12 min on screen31 min totalNeeds your eyes
- The Chrome team explains WebMCP with real demos: register tools on your site so agents can stop screenshotting and clickingTara Agyemang · AI Engineer World's FairFor · Front-end and full-stack developers / Website tech leadsAgentAI Product12 min on screen22 min totalNeeds your eyes
- A hands-on audio AI class carried almost entirely by live demos, from transcription to singingThor Schaeff · AI Engineer World's FairFor · Choosing a real-time voice stack / Voice feature developersAI ProductAgentAI Coding12 min on screen20 min totalNeeds your eyes
- Same model, only the harness changed — the score jumped more than 20 points. The evidence and the how-to are both in this talk.Aditya Bhargava · AI Engineer World's FairFor · Developers building their own agents / Anyone deciding which model to useAgentAI CodingEvalsContext13 min on screen32 min totalNeeds your eyes
- Real eval scores on screen: the full loop for letting a coding agent tune an AI agentAlfonso Graziano · AI Engineer World's FairFor · AI application engineers / Tech leadsAgentEvalsAI Coding13 min on screen30 min totalNeeds your eyes
- A production-grade blueprint: how a design system becomes infrastructure AI agents can consume directly, and turns into $1 billion in business results.Emily · Figma ConfigFor · Design system maintainers / Front-end platform engineersDesign-to-CodeAgentContextAI CodingAI Product13 min on screen21 min totalNeeds your eyes
- A three-step method road-tested on SAP's complex design system: turn your design system into a Kit and templates that Make will actually use.Laura · Figma ConfigFor · Design system maintainers / DesignOps leadsDesign-to-CodeAgentContextAI Product14 min on screen30 min totalNeeds your eyes
- Cursor's CEO on the agent-first shift, plus a first look at a frontier model trained from scratchMichael Truell · Cursor CompileFor · Tooling decision-makers / Agent workflow designersAgentAI CodingAI Product14 min on screen27 min totalNeeds your eyes
- Prime Intellect's applied research lead opens up the whole open-source RL stack: the real cost sheet for a $50K full RL run on a frontier modelWill Brown · AI Engineer World's FairFor · RL training engineers / Technical decision-makersAgentEvalsAI Coding15 min on screen47 min totalPart listen, part watch
- Ten thousand notes in practice: drop the vector database, let plain markdown make your knowledge reusable by agentsPaul Iusztin · AI Engineer World's FairFor · Engineers building their own memory layer / Heavy second brain usersAgentContextAI Coding15 min on screen40 min totalPart listen, part watch
- Psychometrics moves into LLM evals: flag the bad items, cut 80% of the questions, and detect distillation kinshipAlejandro Vidal · AI Engineer World's FairFor · Benchmark maintainers / Whoever decides which model to useEvals17 min on screen24 min totalNeeds your eyes
- The Local AI inflection point in an hour: once a GPT-4o-class model runs on your phone, privacy and cost start rewriting the industry.Alex · AI Engineer World's FairFor · Anyone evaluating local deployment / Whoever owns the AI budgetAgentAI CodingAI ProductContext19 min on screen44 min totalNeeds your eyes
- An OpenAI engineer's argument: every agent sandbox ends at micro VMs — skip two years of grief.Abhishek Bhardwaj · AI Engineer World's FairFor · Sandbox infrastructure engineers / People choosing a platform for agentsAgentAI Coding20 min on screen45 min totalNeeds your eyes
- AI accelerates execution, not clarity; precise context gets agents writing less, and writing it betterJake · Figma ConfigFor · Design system maintainers / Design engineersAgentAI CodingContextDesign-to-Code20 min on screen32 min totalNeeds your eyes
- Build a plugin with one sentence: Figma's full demonstration of handing tool-making back to designers.Georgia · Figma ConfigFor · Designers who want to change their workflow / Plugin developersAgentAI CodingAI Product21 min on screen33 min totalNeeds your eyes
- A reproducible experiment proves it: your character-AI evals can't catch a Hamilton who has read his own Broadway musicalJacob E. Thomas · AI Engineer World's FairFor · Eval leads for character AI / Prompt engineering leadsEvalsContextAI ProductAgent25 min on screen58 min totalNeeds your eyes
- RAG running live on an all-free local stack, proving clean chunking decides more than a big modelAbed Matini · AI Engineer World's FairFor · Engineers shipping RAG / Teams limited by budget and complianceContextAgentAI Product26 min on screen46 min totalNeeds your eyes
- Five kinds of agent hallucination, five code demos run live side by side, all open source and reproducibleElizabeth Fuentes · AI Engineer World's FairFor · Engineers productionizing agents / Agent platform architectsAgentContextEvals42 min on screen55 min totalNeeds your eyes