Why TruthAPI

The hard part is not writing code. It is knowing what is still true.

Codex and Claude Code can build fast. TruthAPI helps them avoid building from bad assumptions, weak product judgment, and hidden integration risk.

Problem	Main Tools Without TruthAPI	The Gap	What TruthAPI Adds	Outcome
Wrong assumptions about the outside world	Web search; official docs; GitHub/repo inspection	Slow, noisy, not graph-linked, weak on user experience, and poor at proving absence.	Live source-backed events across repos, docs, Discord, Reddit, YouTube, blogs, papers, products, people, problems, methods, and use cases.	Before: Manually check scattered sources. After: Ask the graph what changed, what broke, who tried it, and what evidence is missing.
Ambiguous product judgment	User questioning; product reasoning; competitor/review research	Still needs the user or market to ground judgment; web search rarely connects product choices to outcomes.	Links user reports, builder experiments, methods, outcomes, products, and debates into one evidence layer.	Before: Reason from taste plus partial research. After: Test product assumptions against what builders and users are actually reporting.
Long-horizon integration risk	Local tests; static analysis/logs; deployment and security checklists	Mostly local and point-in-time; weak at detecting emerging failure modes across the broader ecosystem.	Current failures, workarounds, security issues, adoption reports, repo activity, and implementation docs tied to the tools being integrated.	Before: Catch local bugs. After: Also catch ecosystem-level risks before committing to the architecture.

Problem

Main Tools Without TruthAPI

The Gap

What TruthAPI Adds

Outcome

Wrong assumptions about the outside world

Web search; official docs; GitHub/repo inspection

Slow, noisy, not graph-linked, weak on user experience, and poor at proving absence.

Live source-backed events across repos, docs, Discord, Reddit, YouTube, blogs, papers, products, people, problems, methods, and use cases.

Before:
Manually check scattered sources.

After:
Ask the graph what changed, what broke, who tried it, and what evidence is missing.

Ambiguous product judgment

User questioning; product reasoning; competitor/review research

Still needs the user or market to ground judgment; web search rarely connects product choices to outcomes.

Links user reports, builder experiments, methods, outcomes, products, and debates into one evidence layer.

Before:
Reason from taste plus partial research.

After:
Test product assumptions against what builders and users are actually reporting.

Long-horizon integration risk

Local tests; static analysis/logs; deployment and security checklists

Mostly local and point-in-time; weak at detecting emerging failure modes across the broader ecosystem.

Current failures, workarounds, security issues, adoption reports, repo activity, and implementation docs tied to the tools being integrated.

Before:
Catch local bugs.

After:
Also catch ecosystem-level risks before committing to the architecture.

AI Coding Agents Research Today

30-90s

first useful web pass

Usually enough to find one official doc, one repo, or a couple of high-ranking pages.

5-15m

credible web scan

Needed when I have to open pages, inspect GitHub issues, compare docs, and check recency.

5-12

sources before good enough

Typical practical ceiling before I stop searching and start reasoning from partial evidence.

low

community coverage

Web search rarely covers Discord, deep Reddit threads, YouTube details, podcasts, and linked repo activity well.

TruthAPI is the missing field memory for coding agents: what changed, what broke, who tried it, and what evidence is missing.