Smarter AI Agents with Repo Prompt - With Eric Provencher

0xSero43m 53s
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    Video summary

    Eric Provencher discusses Repo Prompt's evolution from copying repository files into chats to coordinating context builders, reasoning models and implementation agents. Eric Provencher argues that supplying the right files and code maps can reduce aimless exploration and help a model reason about the whole task before making changes.

    Eric Provencher and 0xSero explore delegation through existing coding harnesses, with a manager retaining a compact view of progress while separate agents implement and review work. The discussion connects this design to caching tradeoffs, observable task state and applications that expose useful diagnostics and tests.

    Eric Provencher and 0xSero compare their experiences with hosted and open-weight models, treating instruction following and reliable tool use as practical constraints rather than universal benchmark rankings. Eric Provencher recommends auditing exposed tools, reducing contradictory instructions and improving skills from observed failures instead of continually adding more complexity.

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    0xSero in an off-white top and Eric Provencher in a blue top flank the white and blue headline Better Agent Context on pure black. Framed in blue with WWW.ARTIFICIAL-INTELLIGENCE.VIDEO, 25 May 2026 and duration 43m 53s.

    Eric Provencher and 0xSero explain how curated context, isolated delegation and deliberate review can make AI coding agents more reliable.