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Async Agents Need More Than a Coding Model …support: staff tag an issue, let the agent collect diagnostic context, then bring engineering into the conversation with fewer requests for more information. - Security work: agents perform continual scanning and review. Devin’s auto triage… Writeup · Date unavailable	Writeup	—	—
Autonomous Drones: From a Lost Video Link to Mass Deployment …replacing the platform. In the Latent Space conversation, that engineering thesis accompanies a moral commitment. Azhnyuk presents resistance to invasion as an obligation and weapons developers as support for those doing the fighting. A… Writeup · Date unavailable	Writeup	—	—
Axiom’s Bet: Make Reasoning Checkable, Then Scale It …the researcher. The software vision applies decomposition to engineering. A general assistant such as Claude might break down a distributed system and call Axiom for a component it can tackle. Axiom would return a formally verified… Writeup · Date unavailable	Writeup	—	—
Benchmarks, Self-RAG, and Step-by-Step Verification — Part 3 of 5 …for the ongoing measurement effort. He also credits the engineering behind evaluation infrastructure, including the Eleuther Evaluation Harness underlying the OpenLLM Leaderboard. Dynamic benchmarks evolve by incorporating newly discovered … Writeup · Date unavailable	Writeup	—	—
Beyond the Model API: Tools, Labor, and Expressive Voice — Part 2 of 3 …analysis. They want comparable clarity for AI application engineering: tools that help explain what to change. The proposed LLM operating system is a surrounding set of building primitives that goes beyond prompt-call helpers and… Writeup · Date unavailable	Writeup	—	—
Beyond the Prompt Box: Building Notion AI’s Interfaces …- Knowledge synthesis: search, interpret, and combine existing context. - Automation: propose actions or generate code that accomplishes a task. The proposed progression follows the work behind a document. Much knowledge work aims to… Writeup · Date unavailable	Writeup	—	—
Bolt.new: Making the Development Environment Part of the Agent …environment for it. He subsequently led WebContainer engineering and then the team’s AI work. That shared context, the speaker argues, helped a small group connect implementation decisions quickly. The reported arrival of roughly… Writeup · Date unavailable	Writeup	—	—
Brightwave: financial research built from bounded AI systems …a disappointed expectation: in the team’s experience, larger context windows did not reliably produce deep synthesis across disparate material. Recovering a fact and integrating evidence are different capabilities. A needle-in-a-haystack… Writeup · Date unavailable	Writeup	—	—
Building agents that can find, fix, and verify their work …the requested behavior—but Schluntz valued their origin in real engineering work. That realism costs time and tokens. An attempt may read substantial repository context, write code, run it, and revise it repeatedly. Schluntz therefore… Writeup · Date unavailable	Writeup	—	—
Building AGI in Real Time — Part 3 of 3: From Model Capability to Useful Agents …coverage beyond what staff could manually inspect. The engineering emphasis is performance of the end-to-end workflow. A respondent describes connecting models with different strengths so the overall process can work well despite mistakes… Writeup · Date unavailable	Writeup	—	—
Building an Email Agent That Finishes the Work …informs his advice to European founders: build on strong engineering education with greater emphasis on product creation, growth, organizational scaling and ambition. He encourages serving English-speaking users globally from the outset,… Writeup · Date unavailable	Writeup	—	—
Building Company Intelligence: Private Evals, Open Harnesses, and Agents That Run the Work …tools progressively to improve token efficiency. Preparing rich context—the information an agent needs for its task—is a major determinant of whether its plan executes efficiently. The respondent says Microsoft uses a GitHub harness across … Writeup · Date unavailable	Writeup	—	—