About Toket AI
Exploring how products are built in the AI era.
Toket is an independent AI product lab — my long-term experiment on how humans and AI work together: from cost judgment and prompt clarity to model choice and real workflows.
Builder
Siji Wang
Independent AI Product Builder
Creator of Toket AI
I am less interested in shipping another AI feature than in how products are actually built in the AI era: judgment, validation, iteration, and notes in public.
Toket grew from concrete friction: unclear tasks, invisible cost, and hard model choices — the work stalls before the first model call.
So I am building Toket as a long-term experiment: small product bets, Lab Notes in public, and a continuous search for how people and AI work together.
Why Toket exists
AI tools are everywhere. Building the product is the hard part.
Before a model can help, people still need to clarify the task, choose the right model, understand the cost of trying, and decide whether failure needs a better prompt or a different path.
Toket turns those judgments into product capabilities: clearer tasks, visible cost, and choices that can be explained.
Software is shifting from feature menus to task systems. An entry point is not enough — work needs context, tradeoffs, fewer retries, and assets that can keep moving.
What Toket builds
A clearer path for AI work.
Product discovery lives mainly on the homepage and the AI Model Directory. This is only the shortest map.
- AI Cost Analysis See token and cost signals before expanding usage.
- Prompt Optimizer Turn vague work into clearer prompts.
- Workspace · Private Beta Keep context, model choice, and results inside one workflow.
- AI Models Understand the model before choosing the model.
- Model Roast A lightweight Lab experiment for naming AI frustration — then return to real tasks.
Make the judgment clearer first.
- Understand the model before choosing the model.
- Estimate cost before expanding usage.
- Clarify the task before chasing output.
- Turn one-off AI calls into workflows.
Still validating
Toket will keep running lightweight product experiments around:
- AI cost visibility and model choice
- Prompt quality and task clarity
- Lab and Workspace efficiency
Build in public
Lab Notes document how Toket is growing.
These are original notes about product decisions, experiments, and lessons learned — not industry news.
No published Lab Notes yet. Visit the Lab Notes hub for updates.
Start with a real task
Clarify one task first.
Start with cost planning or prompt optimization. To follow the building process, read Lab Notes. To collaborate, reach out directly.