Cool AI tools — but organized like an operator.
This is a Learning Center page: decision rules + starter stacks. For implementation/service-ready stacks, use AI Tools (Services). For the broader learning directory, use Cool AI Tools.
The hub rules (why this isn’t another “best tools” page)
Every section answers: use / ignore / avoid.
Tools are ranked by outcomes. If it doesn’t improve speed, quality, or control, it’s noise.
Work ships in pipelines.
Combinations win: generate → edit → assemble → publish → govern.
If you can’t evaluate it, you can’t trust it.
Real workflows need gates, testing, and traceability — not vibes.
Generator creates raw output.
Director controls and edits output.
Assembler / Governor stitches + prevents mistakes.
iWasGonna Picks (starter set)
Not a complete list — a default kit. If you’re overwhelmed, start here and only expand when you hit a real constraint.
ChatGPT
- Use for: planning, drafting, structured thinking, ops docs
- Rule: verify claims that matter (money, policy, health, customer comms)
Claude
- Use for: longform editing, structured reasoning, rewriting systems
- Rule: treat as co-writer, not a source of truth
Gemini
- Use for: Google ecosystem workflows and quick iterations
- Rule: keep governance when decisions are high-stakes
Perplexity (or equivalent)
- Use for: source-linked research, fast landscape scans
- Rule: open the sources — don’t trust summaries blindly
Cursor (AI-native editor)
- Use for: shipping code faster with context
- Rule: tests + reviews or you’ll scale bugs
Zapier / n8n / Make
- Use for: connecting apps, routing leads, content pipelines
- Rule: mission-critical flows need logs + retries + ownership
Want the “service-grade” version of these (with governance gates, approvals, and monitoring)? That lives on /ai-tools/.
Categories
Pick the job you’re trying to do. Then pick a stack.
High-fidelity video generation
- Generators: Kling, Sora, Veo, Luma
- Directors: Runway (edit/control)
- Use for: ads, cinematic shots, product visuals
Talking head + translation
- Generators: HeyGen, Synthesia
- Use for: UGC-style ads, training, multilingual content
- Watch: consent, rights, likeness rules
Images, vectors, layouts
- Generators: Midjourney, Ideogram
- Governed: Adobe Firefly
- Assembler: Canva
Voiceovers, cleanup, sound
- Generator: ElevenLabs
- Director: timeline tools
- Cleanup: Adobe Podcast, Krisp
Build, automate, ship
- Developer: Cursor
- Automation: Zapier, n8n, Make
- Systems: docs + trackers + SOPs
Prevent expensive mistakes
- Eval/Tracing: LangSmith
- Testing: Promptfoo
- Rule: approvals before publish/send
Cinematic video (Generators + Directors)
The win is coherence: consistent characters, stable environments, believable motion. Generate first. Then direct/edit into something usable.
- You need ad-ready shots, scenes, or b-roll fast
- You can tolerate iteration (generate → pick → refine)
- You want “director control” without a full VFX pipeline
- You need frame-perfect continuity across long sequences
- You have strict compliance constraints on visuals
- You already have a reliable human video team
- Identity drift kills trust
- Prompt chaos = costly iteration
- Rights/usage confusion when teams reuse assets
Kling
- Use for: dynamic motion + ad shots
- Note: pair with a Director tool for refinement
Runway
- Use for: editing, control, iteration
- Rule: it’s an editing suite, not “one prompt” magic
Sora / Veo / Luma
- Use for: concept testing + cinematic realism
- Note: availability/workflow varies over time
Avatars & localization (marketing at scale)
Business use case: personalized video without film crews. Business risk: consent + brand trust.
- You need multilingual training/marketing fast
- You want UGC-style creatives at volume
- You have a review/approval workflow
- Your brand relies on real creators
- You can’t control script approvals
- You’re unclear on likeness permissions
- Bad scripts scale embarrassment
- “Uncanny” delivery can lower conversion
- Likeness misuse = legal + reputation damage
HeyGen
- Use for: marketing avatars + localization
- Rule: add a script-quality gate
Synthesia
- Use for: training + corporate explainers
- Bias: consistency over “cinema”
Design & branding (visual quality + licensing clarity)
A 10/10 brand workflow means: great visuals + editable formats + clarity on usage.
Midjourney
- Use for: cinematic images and concept direction
- Rule: keep brand terms consistent
Ideogram
- Use for: thumbnails/posters with readable text
- Rule: spell-check every export
Adobe Firefly
- Use for: client work where licensing clarity matters
- Bias: usable business outputs
Recraft
When you need icons/logos that scale, vector-first reduces redesign work.
Canva
Where assets become deliverables: social packs, one-pagers, thumbnails, decks.
Voice & audio (realism, cleanup, production speed)
The edge is consistent delivery + studio-quality cleanup from imperfect recordings.
ElevenLabs
- Use for: voiceovers, narration, character reads
- Rule: permissions and voice rights matter
Murf (or timeline tools)
- Use for: structured edits and syncing voice to video
- Bias: control over “more voices”
Adobe Podcast / Krisp
- Use for: meetings, podcasts, interviews
- Rule: don’t over-clean and kill natural tone
Productivity, coding, and automation
The shift is from “AI helps me type” to “AI executes a workflow.”
Notion / Google Workspace
- Use for: SOPs, trackers, briefs, knowledge
- Rule: one source of truth per process
Cursor
- Use for: shipping code with an AI-native editor
- Rule: tests + reviews before deploy
The governance layer (how you avoid expensive mistakes)
If you can’t evaluate it, you can’t trust it. This is what keeps “confident wrong” from becoming policy by accident.
- You’re deploying AI inside a business process
- You need repeatable results (not “sometimes good”)
- You care about audits, accuracy, or customer trust
- You’re doing personal creative exploration only
- Failure has zero cost
- You don’t care about reproducibility
- Hallucinations become “truth” by repetition
- Silent model changes break workflows
- Confident wrong answers damage customers
LangSmith
- Use for: debugging chains, eval workflows
- Rule: run real traffic to get value
Promptfoo
- Use for: regression testing across model changes
- Rule: maintain “golden” test cases
Approval gates
- Use for: outbound messages, compliance outputs
- Rule: no gate = accident machine
Enforce approvals via Zapier/n8n before actions.
Recommended stacks (choose one and ship)
Stop buying random subscriptions. Pick a stack aligned to your reality.
Goal: speed + volume
- Video: Kling → Runway
- Voice: ElevenLabs
- Design: Canva
- Automation: Zapier (light)
Best when “done today” beats “perfect later.”
Goal: consistency + localization
- Avatars: HeyGen / Synthesia
- Design: Firefly → Canva
- Audio: Adobe Podcast / Krisp
- Ops: Zapier or Make
Best when you need repeatable output across campaigns.
Goal: safety + traceability
- Design: Firefly (safer)
- Automation: n8n (controlled)
- Governance: LangSmith + prompt tests
- Rule: human approvals before publish/send
Best when trust is the product.
Next move: convert tools into a governed system
Access isn’t the advantage anymore. Orchestration, restraint, and judgment is. Use the Learning Center for decisions — use Services when you want implementation.
This hub is intentionally opinionated. Add tools only when they earn a place by outcomes.