Section 10.2.9 : Evaluate and iterate — FACTS criteria
🎯 Learning objective
Developing a systematic method to evaluate AI response quality and iterate effectively until obtaining a usable result. Mastering the FACTS framework and iteration strategies to never again accept a mediocre response.
The trap of passive acceptance
The biggest risk with generative AI isn't that it's wrong — it's that you accept its response without critical evaluation. A good AI practitioner never takes the first response at face value.
Why this trap is so common:
- →AI produces fluent and confident responses — the "expert" tone creates an illusion of competence
- →Cognitive fatigue pushes us to accept the first response when it's "roughly correct"
- →Automation bias: we place excessive trust in automated systems
- →The cost of iteration seems high — but it's always lower than the cost of using a mediocre result
In reality, the difference between an average AI user and an expert AI user comes down to one word: iteration. The expert systematically evaluates and iterates 2-3 times. The average user takes the first response.
FACTS criteria: your evaluation framework
Fidelity — Actionability — Completeness — Tone — Structure
| Criterion | Question to ask | Red flags to detect | Target score |
|---|---|---|---|
| F — Fidelity | Is the information accurate and verifiable? | Overly round numbers, uncited sources, excessive generalizations, incorrect dates, invented names | 9/10 minimum |
| A — Actionability | Can I act concretely with this response? | Vague advice ("you need to innovate"), no next steps, no identified owner | 8/10 minimum |
| C — Completeness | Are all aspects of my request covered? | Ignored questions, missing perspectives, untreated edge cases | 8/10 minimum |
| T — Tone | Is the tone appropriate for my audience? | Too academic, too casual, inconsistent, condescending, unnecessary jargon | 7/10 minimum |
| S — Structure | Is the format clear and well-organized? | Wall of text, confusing hierarchy, no summary, missing headings | 8/10 minimum |
Scoring in practice:
- →Total score ≥ 40/50: the response is usable as-is
- →Score 30-39: a targeted iteration will suffice
- →Score < 30: reformulate the initial prompt — iteration won't be enough
The most often ignored criterion: Fidelity
Fidelity (F) is the most critical and most neglected criterion. AI can produce perfectly structured, well-toned, actionable, and complete responses — but factually wrong. This is the hallucination phenomenon.
Quick verification technique:
- →Ask "What are your sources for this information?"
- →Verify key figures on Google (30 seconds)
- →If a statistic seems too perfect to be true, it probably is
- →Dates, people's names, and exact quotes are the highest risk
The 5 iteration strategies
Strategy 1: Surgical iteration — Target the specific problem
The most effective and fastest. Precisely identify what's wrong and request a surgical correction.
Good response overall, but 3 adjustments needed:
1. The pricing section is too vague. Replace
generic ranges with concrete prices
for the French market in 2026:
- Starter: [exact range]
- Pro: [exact range]
- Enterprise: [exact range]
2. The tone is too academic for my audience (SMBs,
non-technical executives). Reformulate paragraphs
3 and 5 in direct business language, no jargon.
3. The legal dimension is completely missing.
Add a paragraph about GDPR and compliance
obligations.
Keep everything else identical.
Strategy 2: Forced self-evaluation — Have the AI critique itself
Powerful technique when you're not sure what's wrong. The AI often identifies weaknesses you wouldn't have seen.
Reread your response above and rate it from 1 to 10
on each FACTS criterion:
- F (Fidelity): /10 — is the information verifiable?
- A (Actionability): /10 — can someone act immediately?
- C (Completeness): /10 — are all aspects covered?
- T (Tone): /10 — appropriate for the target audience?
- S (Structure): /10 — clear and well-organized?
For each score < 8:
1. Explain the weakness precisely
2. Propose a concrete improvement
3. Rewrite the relevant section
Then produce the final version integrating all
improvements.
Strategy 3: Confrontation iteration — Simulate critical external feedback
Ideal when the response seems "correct" but lacks depth. We simulate feedback from a demanding expert.
You show your response to 3 people:
1. A domain expert (15 years of experience) who says:
"This is superficial. A junior could write this."
2. The CEO who says: "Where are the numbers?
I can't make any decision with this."
3. A client who says: "Concretely, what do I do
Monday morning at 9 AM?"
Rewrite your response addressing each criticism:
- More technical depth (expert)
- More quantified data (CEO)
- More concrete step-by-step actions (client)
Strategy 4: Perspective shift — See the problem differently
When classic iteration isn't enough, change the angle of attack.
Your previous response approached the subject from
the [PERSPECTIVE A] point of view. Now, rewrite it from
the perspective of:
1. A skeptic who doubts every claim
2. A complete beginner with no context
3. A competitor looking for flaws
Then merge the 3 perspectives into a balanced response
that anticipates objections.
Strategy 5: Subtraction iteration — Make it more concise
Often, the problem isn't missing content — it's too much. The superfluous drowns the essential.
Your response is [X] words. Rewrite it in [X/2] words maximum
by removing:
- Everything obvious or already known to the audience
- Unnecessary transitions and filler phrases
- Redundant examples (keep the best of each category)
- Empty qualifiers ("very", "really", "quite")
Rule: each remaining sentence must provide information
the reader didn't have before reading it.
The 4-step iteration workflow
Concrete iteration examples
Case 1: The too-vague report
Initial prompt: "Analyze SaaS market trends in France"
- →F: 5/10 (unsourced figures), A: 4/10 (no recommendations), C: 6/10 (B2C ignored), T: 8/10, S: 7/10
- →Score: 30/50 → Surgical iteration needed
Iteration:
Good foundation, but needs 3 major corrections:
1. FIDELITY: cite your sources for each figure.
If you don't have a source, indicate "estimate"
and give the range.
2. ACTIONABILITY: for each identified trend,
add "What this means for a French SaaS SMB:
[concrete action]".
3. COMPLETENESS: you ignored the B2C segment and the
vertical market. Add a section on each.
Case 2: The too-gentle code review
Initial prompt: "Do a code review of this Python file"
- →F: 8/10, A: 5/10 (vague suggestions), C: 3/10 (security absent), T: 9/10, S: 7/10
- →Score: 32/50 → Confrontation + surgical
Iteration:
Your review is too lenient. A senior lead engineer
would read it and say: "You didn't check security
and your suggestions don't contain corrected code."
Redo your review adding:
1. Complete SECURITY section (SQL injection, XSS, auth,
exposed sensitive data)
2. For EACH identified problem: the current code AND
the corrected code, not just a description
3. A summary table with severity and priority
Practical exercise: The FACTS challenge
Duration: 20 minutes
- →Take a recent AI response you've used in your work
- →Rate it on each FACTS criterion (F, A, C, T, S) from 1 to 10
- →For each score < 8, write a targeted iteration prompt
- →Send the iterations and compare V1 and V2
- →Does V2 have a score ≥ 40/50? If not, try the confrontation strategy
What does the 'A' in the FACTS evaluation criteria for AI responses stand for?
After evaluating an AI response at 28/50 on the FACTS framework, what should you do?
Learn AI, from prompts to agents