For engineers

Self-improving context for AI agents

Alignbase gives your team one place to manage agent context. Define your team-wide AGENTS.md and Skills, then watch as each agent's learnings improve the whole fleet.

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Coding agents don't learn as a team.

One agent finds the missing test setup, fixes a release gotcha, or learns a customer constraint. The next agent starts cold unless that learning becomes shared context.

  1. Cold start

    Each agent starts without approved team context

    The rule that changes the implementation may live in a repo note, team decision, customer promise, or Skill the agent never sees.

  2. Lost learning

    One agent learns it, the fleet does not

    An agent finds the test setup, fixes a release gotcha, or learns a customer constraint. The next agent starts cold again.

  3. Context drift

    AGENTS.md files and Skills age in different places

    Local files, copied Skills, and wiki snippets drift apart as teams move. Agents can use stale instructions even when the team has learned better.

  4. Review tax

    Your review becomes context repair

    Plausible code can still miss team standards, customer constraints, or rollout plans. Review becomes context repair.

AGENTS.md, Skills, and knowledge bases aren't enough.

AGENTS.md can't improve the whole fleet

Repo-local AGENTS.md files are useful, but teams need one place to update context and improve agent output across all users, repos, and branches.

Skills need governed access

Skills are useful optional context, but teams need control over which agents can read, install, update, and use them. Local copies drift, and broad access hides what an agent could use.

Knowledge bases are too big

Knowledge bases are broad, noisy, and often out of date. Agents have very limited context windows and lose the important pieces of context in the noise.

Strategy context
Policy context
Testing skill
Eve's agent
Eli's agent
Jake's agent

Turn agent learnings into managed context.

Alignbase is the single source of truth that brings authentication, permissions, versions, reviews, and audits to your context.

Context your agents should start with:

  • → Company overview, strategy, and KPIs
  • → Product description, vision, and ICP
  • → Security, privacy, and compliance rules agents should not miss
  • → Cross-repo architecture decisions and active migrations
  • → Engineering standards and review policy that apply across teams
  • → Active outages, incidents, and maintenance windows

Skills your agents should have available:

  • → Testing notes, commands, and fixtures
  • → Release and rollback procedures
  • → Design system rules and component examples
  • → Security review checklists
  • → Customer-specific implementation notes
  • → Scripts, templates, and task-specific references

When you centralize context, you get:

  1. Governance

    Context management

    Centralize context and Skills in one approved place with owners, reviews, permissions, and audit history.

  2. Accuracy

    Aligned agents

    Every coding agent your team uses starts from the right current context and uses the latest approved Skill version every time.

  3. Learning

    Fleet-wide improvements

    Useful agent learnings can become reviewed, versioned context or Skills that every matching agent uses later.

  4. Efficiency

    Token savings

    Agents spend fewer tokens exploring dead ends and redoing work.

Start improving agent context in minutes.

Connect the agents you and your team already use, then keep their context and Skills current without changing your workflow.

  1. Step 1

    Open Alignbase

    Create an account to initialize your team-wide context repository.

  2. Step 2

    Define context and Skills

    Add your AGENTS.md, Skills, policies, and operating context your agents should share.

  3. Step 3

    Connect an agent

    Give agents the latest approved context, then publish useful learnings back to the fleet.

Company Strategy
Eng Policies
Sales Policies
Division 1 KPIs
Division 2 KPIs
Team A Architecture
Team B Architecture
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Questions engineers ask.

Short answers about how Alignbase fits with AGENTS.md, Skills, wikis, and the coding agents you already use.

What is AI coding agent context?
AI coding agent context is the product, policy, customer, architecture, and team knowledge an agent needs to implement work correctly. Repo-local commands and conventions still belong in repo AGENTS.md files. Alignbase is for team and cross-repo context those files cannot manage well.
How is Alignbase different from AGENTS.md?
AGENTS.md is useful for repo-local rules, commands, and conventions. Alignbase gives teams a managed AGENTS.md layer with Skills, reviews, versions, permissions, and audit history, so useful updates can improve the whole agent fleet.
Does Alignbase replace repo-level AGENTS.md files?
No. Repo-level instructions are still useful for local commands and codebase rules. Alignbase adds the team context that lives outside one repo, then routes the right bundle and Skill access to each agent. A team can be a squad, function, or whole company.
How do Skills fit into Alignbase context?
Some context should be loaded when an agent starts. Other context should be available only when the task calls for it. Alignbase manages both, with tags, permissions, versions, and audit records.
What does self-improving context mean?
It means useful agent learnings can become reviewed, versioned context or Skills that other agents use later. The team keeps control through permissions, reviews, and audit history.
Why not just point agents at a knowledge base?
Knowledge bases are usually too broad, noisy, and stale for agent startup context. Alignbase gives agents approved context with permissions, reviews, audits, version history, and fine-grained edit rules.
Which engineering context should go into Alignbase?
Good starting points include product goals, customer constraints, security rules, cross-repo architecture decisions, active migrations, rollout plans, incidents, and review policy that applies beyond one repo.
What benefits should engineering teams expect?
Alignbase gives teams context governance, aligned agents, fleet-wide improvements, and token savings from building the right thing in fewer iterations. Engineers spend less time repairing missed context because useful updates can become shared context or Skills.
How do teams start?
Start with one team, service area, or repeated workflow where coding agents miss team-level context. Open Alignbase, define the AGENTS.md and Skills those agents should share, connect an agent, and publish useful learnings back to the fleet.