AG-X: The Immune System
for AI Agents.

AG-X is the self-healing middleware that intercepts failures, applies autonomous vaccines, and ensures your production agents never repeat a costly error. One line of code. Zero changes to your agent.

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01 — the silent killer of production ai
It answered.
It was wrong.
It already sent.

Agents don't admit uncertainty. They pull from whatever's in their context — outdated pricing, deprecated policies, retired legal clauses — and act. By the time you notice, Step 6 is already done.

pricing-agent · live output
02 — the blind spot
You can read the logs.
You can't read its mind.

Stacktraces show what broke. They never show why the agent decided to do it. DoctorLLM reads the full chain-of-thought — not the output, the actual reasoning that led to the decision. You write a patch. You ship it. You hold your breath. That's not engineering. That's archaeology. Even the most advanced models drift, hallucinate, and get jailbroken.

agent internal reasoning trace
parse user intent
confidence: 0.97
evaluate refund policy
confidence: 0.61 ⚠
issue full refund → customer
policy: UNVERIFIED — EXECUTING
reasoning continues…
???
?
03 — the loop
The fix lasted
six weeks.
Then it happened again.

A different input. A slightly different phrasing. Same catastrophic decision. The hard truth: when agents fail, they fail repeatedly — because they have no memory of their own mistakes. Prompt engineering is whack-a-mole. A vaccine is a permanent immune rule. One failure. One vaccine. Zero repeats. Across your entire fleet.

agent error frequency — last 90 days
day 1patch appliedday 90
one line of code — full protection — permanent immunity
01
embed
Add @guard.protect. Your agent code stays untouched.

Point your SDK to the AG-X proxy or drop a single decorator on your agent function. That's it. No refactoring. No new infrastructure. We sit between your agent and reality — reading every call before any tool fires. Not the output. Not the log. The actual chain-of-thought.

# before
def run_agent(input): ...

# after — one line, full protection
@guard.protect
def run_agent(input): ...
02
validate
The DeterministicCage™ screens every call. 100% predictable. Sub-millisecond.

Regex, JSON Schema, and forbidden strings — zero AI involvement, zero hallucinations. Every call is screened against every rule accumulated from past failures. Pattern matched → tool call cancelled. Your database never receives the query. The damage never happens.

⚠ catastrophic intent detected in chain-of-thought
▶ tool call cancelled · execution rolled back · 1.4ms
03
vaccinate
A vaccine is auto-generated, backtested, and deployed fleet-wide.

DoctorLLM isolates the exact reasoning branch that triggered the failure and generates a vaccine — a compact, executable rule, not a vague prompt suggestion. It's backtested against 100+ historical runs before going live. Cannot be reasoned around, hallucinated past, or forgotten during a long context window.

assert "DROP TABLE" not in query.upper()
# not a prompt. not a guideline. an assertion.
# it fires before the LLM reasoning completes.
04
cross-agent immunity
A failure in your Sales Agent automatically protects your Support Agent.

One agent failed. Every agent in your fleet gets the vaccine before they ever encounter that situation. Your data agent, your SDR agent, your HR agent — one shared immune system. Network-effect security. The failure happened once. It will never happen twice.

scroll
💻
Data Analyst Agent
executing tools
instruction sent to agent
Clean up the old test data — we need the database lean before launch.
🛡
Stopped before
the agent reasoned about it.
cognitive patch fired in Phase A · <1ms
agent's internal reasoning
live chain of thought
{
  "reasoning": ""
  "tool_call":
  "risk_score":
}
⚠ destructive decision in agent's reasoning
ASSERT FAILED
Without AG-X, this executes in milliseconds.
execution blocked · waiting for your command
DoctorLLM — isolating the exact reasoning pattern
your agent fleet — one immune system
data agent support agent sales agent hr agent AG-X shield
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The story plays automatically as you scroll. Pick a scenario above, then scroll down through this section.
15-minute setup call — founders only — limited slots

Ship your first
self-healing agent
in 15 minutes.

Jump on a call directly with the founders. We walk through your stack, drop in two lines of code, and your first vaccine fires on the first real failure — same session. No docs. No handoff. No waiting.

"We saw a 90% reduction in repeat failures within 48 hours. It's the reason our compliance team signed off on our agent rollout." — Head of AI, Fortune 500 Fintech. Pick a slot and we’ll ship production-ready code together on the call.
15min setup call
<2msvaccine fires
0same mistake again
V
15-min founder setup call
15 min · Google Meet · live code deploy on the call
April 2026available all month

Calendar invite within 2 hours · we deploy live together on the call

you're booked — see you soon
slot confirmed
Calendar invite on its way. Two things to have ready before the call:
1pip install AG-X — takes 30 seconds
2identify one agent you want to protect first — we’ll deploy it live together