Project Setup for Coding Agents
Give coding agents a clearer project to work in.
Every session should have a useful starting point. We organize the project context, rules, and checks that help your team scope agent work, review the result, and continue it later.
Request a project fit reviewNo repository access required for the initial project fit review.
You keep explaining the same project.
Instructions scattered across chats are hard to maintain. Put the decisions that matter beside the project, with clear ownership and links to the code they describe.
Explore ai code cleanup and refactoring- Every session repeats the same investigation before useful work starts.
- Important product decisions live only in old conversations.
- Tasks expand beyond the change you intended to make.
- A handoff says “done” without explaining what was checked or what remains.
A project map. A bounded task. A useful handoff.
Start with a project fit review. If the work is a match, we agree the assessment, access, and implementation scope before making changes.
- 01
Map the working context
Identify the product journeys, key modules, and owners of important rules. Connect the existing instructions and docs to the way your team actually works.
A repository map and a clear home for project guidance.
- 02
Define the change
Create a task structure for the intended behavior, constraints, acceptance criteria, and relevant checks. Record product decisions where future work can find them.
Project-specific instructions and bounded task briefs.
- 03
Make continuation practical
Agree how work is reviewed and handed over. A useful record includes the changed behavior, verification evidence, limitations, and the next action.
A repeatable review and handoff workflow.
A technical assessment is separately scoped. After fit and repository access are agreed, we inspect the agreed system areas and provide prioritized findings, an implementation plan, and acceptance criteria.
Code changes, product completion, testing, and release preparation are a separate implementation engagement with agreed requirements. Sending the review form does not start implementation.
From our own products
Thunderlist: “done” came with a record.
A real task brief, product contract, and verification handoff from our task app show what useful project context looks like.
The engineering problem
An offline workspace could show a cached task and still display a warning about remote preparation. Fixing that warning needed a clear boundary: preserve genuine online failures while treating loss of connection as an expected state.
How the work is organized
The task brief recorded the failure, scope, acceptance criteria, and constraints. The offline flow documented cache and reconnect behavior. The handoff connected the implementation to focused checks and a separate installed-app verification record.
What the record shows
The October 14, 2026 record distinguishes the first unprimed offline fallback from the later known-cache pass. It also names the release checks still open, giving the next reviewer a specific result to continue from.
The installed-app result covers one authenticated workspace with one cached task on one Android emulator. The documents do not establish time savings, guarantee that an agent follows instructions, or close every release criterion.
Thunderlist is Bayon’s own product. These are sanitized summaries of actual engineering records, not a client testimonial.
Explore ThunderlistTask brief
Avoid remote preparation while offline; preserve actionable online failures and recovery.
Product contract
Display cached details when available. A stale cache must not repair authoritative task counters.
Verification handoff
Record the initial fallback, the known-cache pass, and the remaining device and release checks separately.
Before we look at your project.
Which coding tools does this apply to?
The core work concerns your repository and team workflow. Tool-specific instructions are agreed after reviewing the tools and stack you actually use; we do not promise universal compatibility.
Is this a prompt pack?
The deliverables describe your product, its rules, tasks, and checks. They are maintained project context rather than a collection of generic prompts.
Does this include fixing the code?
Missing context and fragile code can need different work. Code changes beyond the agreed setup scope require a separately agreed assessment or implementation engagement.
Will agents work autonomously without review?
The service establishes context and a review workflow. It does not provide a hosted autonomous development team or guarantee that agents always follow instructions. Your release and access decisions remain explicit.
Do you need repository access to start?
No repository access required for the initial project fit review. The initial review does not include a code audit, implemented fixes, or a production-readiness sign-off.
How is the work priced?
Bayon AI service prices are not published on this website. We agree the scope of an engagement before work begins.
Give the next session a better starting point.
Describe your coding tools, the context you keep repeating, and how your team currently reviews changes.
Request a project fit reviewNo repository access required for the initial project fit review.