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Bartholomew
The sub-5µs transactional execution harness for AI agents
Prompt guardrails fail when models get smart. Bartholomew is an inline execution harness for AI agents (Claude, Cursor) that provides atomic 2µs filesystem micro-rollbacks, in-flight secret scrubbing, and offline Merkle audit trails before your OS is touched.
Over the past year, we watched AI agents evolve from conversational assistants into autonomous engines executing shell scripts, modifying codebases, and orchestrating multi-agent swarms.
The problem? LLM prompt guardrails are probabilistic. When an agent enters a runaway loop or attempts an unauthorized file deletion, prompt filters either miss it or return a blunt refusal that sends the agent into a hallucination spiral.
We built Bartholomew (BTP v2.5) as a deterministic execution runtime and transparent MCP security proxy: - Sub-Microsecond OS Event Gating (0.95 µs): Blocks unauthorized desktop clicks and synthetic keystrokes before they hit the OS. - Transactional Micro-Rollbacks: Memory-mapped Copy-on-Write snapshots restore pristine code in milliseconds if an agent acts out of bounds. - In-Flight Secret Redaction: High-entropy keys (AWS, GitHub, OpenAI) are scrubbed from incoming tool arguments and outgoing stdout streams. - Zero-Config MCP Gateway: Works out of the box with Claude Desktop, Cursor, Windsurf, and custom MCP clients.
Would love your brutal feedback, edge-case tests, and questions!
About Bartholomew on Product Hunt
“The sub-5µs transactional execution harness for AI agents”
Bartholomew was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #151 on the daily leaderboard. Prompt guardrails fail when models get smart. Bartholomew is an inline execution harness for AI agents (Claude, Cursor) that provides atomic 2µs filesystem micro-rollbacks, in-flight secret scrubbing, and offline Merkle audit trails before your OS is touched.
On the analytics side, Bartholomew competes within Developer Tools, Artificial Intelligence, GitHub and Tech — topics that collectively have 1.7M followers on Product Hunt. The dashboard above tracks how Bartholomew performed against the three products that launched closest to it on the same day.
Who hunted Bartholomew?
Bartholomew was hunted by ivegotahunnitonit. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Bartholomew including community comment highlights and product details, visit the product overview.
ivegotahunnitonit
Hey Product Hunt! I'm the creator of Bartholomew.
Over the past year, we watched AI agents evolve from conversational assistants into autonomous engines executing shell scripts, modifying codebases, and orchestrating multi-agent swarms.
The problem? LLM prompt guardrails are probabilistic. When an agent enters a runaway loop or attempts an unauthorized file deletion, prompt filters either miss it or return a blunt refusal that sends the agent into a hallucination spiral.
We built Bartholomew (BTP v2.5) as a deterministic execution runtime and transparent MCP security proxy:
- Sub-Microsecond OS Event Gating (0.95 µs): Blocks unauthorized desktop clicks and synthetic keystrokes before they hit the OS.
- Transactional Micro-Rollbacks: Memory-mapped Copy-on-Write snapshots restore pristine code in milliseconds if an agent acts out of bounds.
- In-Flight Secret Redaction: High-entropy keys (AWS, GitHub, OpenAI) are scrubbed from incoming tool arguments and outgoing stdout streams.
- Zero-Config MCP Gateway: Works out of the box with Claude Desktop, Cursor, Windsurf, and custom MCP clients.
Try it with zero install: npx btp-guard or pip install btp-guard.
Academic manuscript & proofs: https://doi.org/10.5281/zenodo.2...
Live demo & docs: https://bartholomew.info
Would love your brutal feedback, edge-case tests, and questions!