We have no dog in the fight.
Except yours.
This page records an idea and proposed language. It does not establish an operating knowledge pool, verified results history, or approved service commitments. It is accessible by link, not a private document.
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Independent perspective. Members first.
Our members deserve a clear view of what works, what falls short, and what to do next.
TenSeconds.ai’s proposed member knowledge pool would bring a neutral, third-party perspective to the people, products, and services involved in an AI project: software providers, consultants, coders, installers, trainers, integration specialists, and compliance vendors, among others.
With permission, we would invite members to share candid assessments of the process from start to finish. What was expected? What actually happened? What did it cost? What would they repeat, change, or avoid?
The membership philosophy is simple: members pay for objective guidance while evaluating, planning, installing, operating, changing, or ending an AI project. The purpose is to put the member’s interests first.
Our one motive: put our members first.
The aim is practical peer-to-peer learning: honest opinions, documented results, recommendations, and lessons learned, with enough context to understand whether another member’s experience applies to your situation.
Members should be able to learn from detailed accounts of real work, including difficult outcomes and unresolved questions. Evidence, firsthand experience, and opinion should each be identified clearly.
AI decisions may be among the most influential choices a business makes in the coming years. Members deserve a place to examine them candidly, learn from one another, and choose their next move.
A member knowledge pool grounded in experience.
Build around permission-based, anonymized accounts that record:
- Expected and actual costs, including internal effort.
- Intended users and sustained usage.
- Expected and measured results.
- Why work continued, changed, paused, or stopped.
- Context that explains whether another member’s experience is comparable.
For later development: define permission and anonymization practices, evidence review, conflicts disclosures, and correction procedures before collecting or sharing accounts. Claims about participation, impartiality, and outcomes need support before use as public sales copy.
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Your proposed member knowledge pool could become especially valuable. Build it around permission-based, anonymized accounts that record:
Expected and actual costs, including internal effort.
Intended users and sustained usage.
Expected and measured results.
Why work continued, changed, paused, or stopped.
Context that explains whether another member’s experience is comparable.
We conduct nurtural 3 party perspective evaluations of software, consultants, coders, installers, trainers, integration, compliance vendors... just to name a few. If a company or service touched one of our members, we request and are usually granted a full and honest assessment of the process from start to finish. There is no ulterior motive, no hidden agenda, you as a member pay us a premium each month for one reason! To stay completely objective when evaluating, planning, installing, operating, changing, or even terminating an AI project. The one ulterior motive we have is but, one to put our members first. Our goal is to offer real, unbiased opinions, results, recommendations, lessons learned, lean too, or stay away from type peer to peer communication. Not three-line, pre-written vendor 'testimonials" posing as natural honest referrals, but true no holds barred truths about the largest and possibly most influential choices you'll make in the next several years.
Saved draft: https://tenseconds.ai/member-knowledge-draft.html