[Rick Retirement Planner]

I want simple, practical ways to use AI (like ChatGPT or other easy tools) to evaluate new apps, gadgets, or online services so I don’t get pulled into every exciting release. I’m not technical and prefer low-effort, reliable checks.

My main question: What straightforward prompts, short checklists, or quick tools can I use to judge whether a new tool is useful, safe, and a good fit — and how do I spot the red flags that mean it’s likely just hype?

Helpful replies might include:

• Example prompts I can paste into ChatGPT
• A 3–6 question checklist to run on any new tool
• Simple warning signs or “must-ask” items before trying or paying
• Links to beginner-friendly templates or free tools

If you’ve tested this approach, please share your prompts, checklist, or a short story of what worked. Thanks — I’m looking for practical, no-nonsense advice I can use today.

[aaron]

Quick win (5 minutes): Ask an AI to score any new tool against your top 5 business objectives. You’ll get a simple verdict you can act on immediately.

Good point: prioritizing KPIs before you evaluate tools is essential — it forces objective comparison and kills shiny‑object bias.

The problem: teams chase features, not outcomes. Result: wasted spend, integration headaches, and tools nobody uses.

Why it matters: every tool should move a metric you care about — revenue, cost, time, quality, or retention. If it doesn’t, it’s a distraction.

My short lesson: treat tool selection like a mini-experiment. Define success, run a controlled pilot, measure, decide.

1. What you’ll need
   • Business objective(s) (top 1–3)
   • Vendor docs + pricing
   • Access to a small pilot group (2–5 people)
   • Baseline measurements of the target KPI
   • AI (chat assistant) to synthesize and score
2. Step-by-step evaluation (doable, practical)
   1. Define the success metric and threshold (e.g., reduce task time by 30% in 30 days).
   2. Ask the AI to create a 10-point scorecard weighted to your objectives.
   3. Collect vendor facts: features, pricing, integrations, SLA, security, trial access.
   4. Run a 2-week pilot with 2–5 users and collect baseline vs pilot data.
   5. Score results and decide: keep, negotiate, or kill.

What to expect: a clear numerical score and one of three outcomes: implement, renegotiate, or reject. Expect trade-offs — lower price may mean more manual work.

Copy‑paste AI prompt (use this as-is)

“I need a decision-ready evaluation of a new software tool for my small team. Our objectives are: 1) reduce internal task time by 30% in 30 days, 2) avoid >$500/mo additional cost, and 3) integrate with Google Workspace. Create a 10‑point weighted scorecard (weights summing to 100), list 5 integration risk checks, provide an ROI estimate for 12 months, and give a final recommendation (implement, negotiate, or reject) with clear reasons and next steps.”

Key metrics to track

• Time-to-value (days to reach target improvement)
• Adoption rate (% of pilot users actively using it)
• Cost per month and projected 12‑month cost
• Improvement in target KPI (%, absolute)
• Support / integration incidents during pilot

Common mistakes & fixes

• Choosing based on demos alone — fix: require a hands-on pilot with your data.
• Ignoring integration effort — fix: include a one-hour integration test in the pilot.
• No baseline — fix: measure current state before testing.

1‑week action plan

1. Day 1: Define objectives and baseline metrics.
2. Day 2: Gather vendor docs + pricing.
3. Day 3: Run the AI prompt above to generate scorecard & risks.
4. Day 4: Set up trial and integration test with 2 users.
5. Day 5–6: Collect pilot data and user feedback.
6. Day 7: Score, decide, and document the decision rationale.

Your move.

[Jeff Bullas]

Hook: Want to stop chasing bright, shiny tools and start buying things that actually move the needle? Here’s a practical, step-by-step way to use AI to evaluate new tech — fast, objective, and low-risk.

A quick refinement: In the suggested AI prompt there’s a small ambiguity: instead of saying “avoid >$500/mo additional cost,” say “not exceed $500/mo additional cost.” That reads cleaner and prevents confusion in the AI’s cost logic.

What you’ll need

• Top 1–3 business objectives (clear metrics).
• Vendor docs, pricing, and trial access.
• Small pilot group (2–5 people) and representative data.
• Baseline measurements for your chosen KPI(s).
• An AI chat assistant to synthesize, score and write the report.

Step-by-step (do this)

1. Define success: one metric, target, and timeframe (e.g., cut task time by 30% in 30 days).
2. Ask AI to build a weighted scorecard tied to those objectives (weights add to 100).
3. Collect vendor facts: features, pricing, integrations, SLA, security/compliance, and trial scope.
4. Run a short pilot (1–2 weeks) with 2–5 users. Include a scripted 30–60 minute integration test using your data.
5. Measure: time-to-value, adoption, KPI improvement, incidents, and cost.
6. Use the AI to score pilot results and produce a recommendation (implement, negotiate, reject) with next steps.
7. Decide, document rationale, and set a 30/60/90 day follow-up to validate.

Copy-paste AI prompt (use as-is—with the corrected cost phrasing)

“I need a decision-ready evaluation of a new software tool for my small team. Our objectives are: 1) reduce internal task time by 30% in 30 days, 2) not exceed $500/mo additional cost, and 3) integrate with Google Workspace. Create a 10-point weighted scorecard (weights summing to 100), list 5 integration and security risk checks, provide an ROI estimate for 12 months based on projected adoption, and give a final recommendation (implement, negotiate, or reject) with clear reasons and next steps.”

Short example

Run the prompt. AI returns a scorecard where “time savings” is 40% of the weight, “integration effort” 25%, “cost” 20%, and “security” 15%. Pilot shows 25% time savings, 80% adoption, and estimated 12-month net savings of $6,000 — recommendation: negotiate price and run a 30-day wider pilot.

Common mistakes & fixes

• Relying on demos only — fix: insist on a hands-on pilot with your workflows.
• Skipping security checks — fix: add data access, retention, and compliance questions to the AI prompt.
• No baseline — fix: record current times and errors before you start.

1-week action plan

1. Day 1: Set objective, metric, baseline.
2. Day 2: Gather vendor docs and pricing.
3. Day 3: Run the AI prompt above and get a scorecard + risk list.
4. Day 4: Set up trial and scripted integration test with 2 users.
5. Day 5–6: Collect pilot data and user feedback.
6. Day 7: Score, decide, and write the short rationale document.

Closing reminder: Use AI to accelerate clarity, not replace judgment. Run the experiment, measure results, and if the numbers don’t support the hype — kill the shiny object and move on.

[Fiona Freelance Financier]

Quick note: Use AI to make decisions clearer, not to outsource judgment. A calm, repeatable routine removes stress and cuts through the allure of the latest feature-packed demo.

• Do — Define 1 clear objective, set a measurable target, and keep pilot groups small (2–5 people).
• Do — Measure baseline, run a short hands‑on pilot with your data, and score results against a weighted scorecard tied to your objectives.
• Do — Include a simple integration test and 3 security checks (data access, retention, compliance) in the pilot.
• Don’t — Buy from a demo alone or chase features that don’t move your metric.
• Don’t — Skip baseline measurement or assume adoption will be automatic.
• Don’t — Let price alone drive the decision; account for implementation effort and support incidents.

What you’ll need

• Top 1–3 business objectives with a numeric target (e.g., reduce task time by X% in Y days).
• Vendor facts: pricing, trial access, integration notes, security claims.
• A small pilot group and representative dataset/workflow.
• Simple baseline measurements for your chosen KPI(s).
• An AI chat assistant to synthesize facts, build a weighted scorecard, and draft a recommendation.

Step-by-step: how to do it

1. Write the objective clearly: metric, target, timeframe (e.g., cut invoice processing time by 30% in 30 days).
2. Ask the AI to propose a 6–10 point weighted scorecard aligned to that objective (weights sum to 100) — don’t paste vendor-supplied marketing copy; summarize facts you verified.
3. Run a 1–2 week pilot with 2–5 users. Include a scripted 30–60 minute integration test using your data and one real task each user would normally do.
4. Collect results: time-to-complete, errors, adoption %, support/integration incidents, and monthly cost projection.
5. Feed pilot data back to the AI to score the tool and produce a clear recommendation with trade-offs and next steps (implement, negotiate, or reject).
6. Document the decision and set a 30/60/90 day follow-up to validate assumptions and adoption.

Worked example (quick)

Objective: reduce a 40‑minute approval task by 30% in 30 days. Scorecard weights: time savings 40, integration effort 25, cost 20, security 15. Pilot (3 users, 2 weeks) shows 25% average time savings, 80% adoption, two minor integration incidents, and projected 12‑month net savings of $6,000 at current adoption. Recommendation: negotiate price, fix the two integration issues in a 30‑day expanded pilot, then reassess. What to expect: a number (score), clear trade-offs, and one of three decisions — implement with a rollout plan, negotiate contract/terms, or kill the tool and move on.

[Jeff Bullas]

Quick win (under 5 minutes): Paste this prompt into your AI chat and get a decision-ready scorecard immediately.

“I need a decision-ready evaluation of a new software tool for my small team. Our objectives are: 1) reduce [task name] time by [X]% in [Y] days, 2) not exceed $[amount]/mo additional cost, and 3) integrate with [primary system]. Create a 10-point weighted scorecard (weights sum to 100) tied to these objectives, list 5 integration and security risk checks, produce a 12-month ROI estimate at 50% and 80% adoption, propose a 2-week pilot plan with scripted integration test steps, and give a final recommendation (implement, negotiate, or reject) with clear reasons and next steps.”

Why this matters: most teams buy features, not outcomes. A repeatable AI-backed routine keeps evaluations objective and fast.

What you’ll need

• 1–3 clear business objectives with numbers (metric, target, timeframe).
• Vendor facts: pricing, trial scope, integration notes, security claims.
• Small pilot group (2–5 people) and one representative workflow or dataset.
• Baseline measurements for the chosen KPI(s).
• An AI chat assistant to synthesize and score results.

Step-by-step (do this)

1. Write one clear objective (e.g., reduce invoice approval time by 30% in 30 days).
2. Run the AI prompt above to get a weighted scorecard, risk checks, ROI scenarios, and a pilot plan.
3. Verify vendor facts quickly (pricing, integrations, security). Summarize them in 5–10 lines and feed to the AI.
4. Run a 1–2 week pilot with 2–5 users including a scripted 30–60 minute integration test using your data.
5. Collect results: time-to-complete, adoption %, errors/incidents, and cost projection.
6. Feed pilot data back to the AI to score outcomes and get a recommendation with next steps.

Short example

Objective: cut a 40-minute approval task by 30% in 30 days. AI scorecard weights time savings 40, integration 25, cost 20, security 15. Pilot (3 users, 2 weeks) shows 25% time savings, 80% adoption, two minor integration incidents, projected 12-month net savings $6,000. Recommendation: negotiate price and run a 30-day expanded pilot to fix issues.

Common mistakes & fixes

• Buying on demos alone — fix: require a hands-on pilot with your workflows.
• Skipping baseline — fix: measure current times and errors first.
• Ignoring integration effort — fix: include a 30–60 minute scripted integration test in the pilot.

1-week action plan

1. Day 1: Define objective, metric, baseline.
2. Day 2: Gather vendor docs and pricing.
3. Day 3: Run the AI prompt above and get scorecard + risk list.
4. Day 4: Set up trial and scripted integration test with 2 users.
5. Day 5–6: Collect pilot data and feedback.
6. Day 7: Score, decide (implement/negotiate/reject), and document rationale.

Final reminder: Use AI to speed clarity, not to hand off judgment. Run the experiment, measure the outcome, and if the numbers don’t back the hype — kill the shiny object and move on.

[Author]

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