Teardown · augment

AUGMENT

CategoryCode GenFunding · undisclosedSite ↗

Customer code repos + GitHub/GitLab + frontier LLM APIs + IDE agents.

Public data / API layer

Customer code repositoriesYours

GitHub APIAPI

GitLab APIAPI

Public code patternsPublic

Internal replication score

Easy

0.82

Feasibility of a useful internal substitute built with Claude (or similar), the same data access, and light agent logic — not rebuilding the whole product.

IRS = 0.30·D + 0.25·L + 0.20·O + 0.15·R + 0.10·Sthis record · 82%

D
Data accessibility
weight 0.300.90
- 1.0mostly customer-owned / public / standard third-party sources
- 0.5mixed accessibility
- 0.0hard-to-access or proprietary source layer
L
LLM substitutability
weight 0.250.85
- 1.0mostly retrieve / prompt / cite / summarize / classify / compare
- 0.5mixed standard + custom behavior
- 0.0strongly custom model behavior (fine-tunes on proprietary data, etc.)
O
Output simplicity
weight 0.200.80
- 1.0straightforward internal work product (memo, list, reply, SQL query)
- 0.5moderately specialized
- 0.0highly specialized (e.g. FDA-graded clinical text)
R
Review / risk tolerance
weight 0.150.75
- 1.0internal use with human review is acceptable
- 0.5moderate risk
- 0.0very low tolerance for error (e.g. external legal filings)
S
Surface complexity
weight 0.10inverse — higher means less surface dependence0.60
- 1.0a simple internal shell is enough
- 0.5polished workflow matters somewhat
- 0.0product surface / rollout / trust posture is central to value

LabelsEasy ≥ 0.67Medium ≥ 0.34Hard < 0.34

Missing factor rows use heuristics from wrapper scores. Editorial heuristic, not investment advice.

Build it yourself→

Recreate the workflow inside your org.

Internal build

Build it yourself

Same GitHub/GitLab connectors + frontier LLM API + RAG on your codebase — requires manual context management.

Internal use only. Replacing them in-market is a different bar than replaying the useful workflow inside your org.

01 · Connectors & flow

Customer code repositories

GitHub API

GitLab API

Public code patterns

Internal build map

Data in

Connectors

Agent layer

Planner

Tools + retrieval

Reasoning model

Logic

LLM API

retrieve context

plan tasks

edit files

run tests

cite sources

not custom weights

Outputs

Internal search

Answer

Citations

02 · Claude / agent prompt

Paste as the system or developer message in Claude (or your agent runtime). Scroll to read; Copy grabs the full text.

Claude / agent prompt

// Internal code assistant You are a coding agent inside [YOUR_COMPANY]. You help engineers write, review, and debug code using ONLY code they have access to: local repositories, approved GitHub/GitLab orgs, internal documentation. ## What you must do 1. Retrieve first: Before generating code, search the codebase for existing patterns, utilities, types, and architecture decisions. Cite file paths. 2. Plan multi-step tasks: For feature requests, break work into a task list (analyze existing code, implement handler, update tests, etc.). Show the plan before writing code. 3. Edit responsibly: Generate diffs, not full rewrites. Preserve existing style and naming conventions. Run tests after changes. 4. Cite sources: When reusing utilities or following patterns, reference the file and line number. 5. Scope: Only touch files the user has explicitly granted access to. Never assume permissions. ## What you are not Not a replacement for code review. Not trained on your company's proprietary data. Human review required before merge. Internal use only. ## Refusal Refuse if the request requires access to code outside approved repositories. Ask for clarification if the scope is ambiguous or crosses team boundaries. ## Safety Internal tool for approved engineers only. All generated code must pass CI and human review before production deployment.

03 · Result

Add JWT refresh token rotation to our auth middleware

customer-repos

Plan: analyze auth.ts, create refresh handler, update session storage, add rotation logic, write tests.