Klydone

AI automation, software & cloud development studio. Building @ResvelleAI.

[Klydone @klydone]

AI usage is not AI ROI.

High activity does not automatically create business value.

The progression that matters:

Usage → paid adoption → revenue → margin → retention

Businesses should measure what AI improves, not simply how often it is used.

At Klydone, we build AI around measurable workflow transformation, not impressive demos.

[Klydone @klydone]

A look at what we’re building at Klydone: @ResvelleAI.

We’re bringing AI chat, tasks, files, brand knowledge and creative tools into one connected campaign workspace.

Still early, but the foundation is taking shape.

More build updates soon 👇

[Klydone @klydone]

Your fintech startup just burned 14 hours on a payments outage…

All because of one misconfigured timeout. Not because the engineers are incompetent.

Because we didn’t have visibility into what was actually failing. Tomorrow we’re running a full failure drill. And here’s the part I’m actually excited about: We’re going to find the next hidden fragility before it costs us millions or trust.

We’re turning yesterday’s outage into tomorrow’s unfair advantage. That’s the difference between teams that survive… and teams that dominate.

Be honest — do you actually know what your team will find in your next failure drill?

Drop your best “we almost missed this… and here’s how we fixed it forever” story below.

Let’s celebrate the ones who ship faster because they break things on purpose.

#Fintech #SRE #Observability #DevOps

[Klydone @klydone]

Drop the one non-negotiable you’d enforce on day one I’m reading every reply. What’s yours?

[Klydone @klydone]

Most teams building AI agents celebrate the demo, then spend six months untangling week-one decisions. Hardcoded prompts. Zero observability.

Agent behavior nobody can explain. Speed and maintainability only feel like enemies when you ignore the tension on day one.

#AIAgents #AgenticAI #LLM

[Klydone @klydone]

1. Treat prompts as versioned code — not strings in config files.

2. Ship observability before the first tool call (OpenTelemetry + LangSmith-style tracing from commit #1).

3. Build a single source of truth for agent state and memory instead of letting every agent reinvent it.

4. Make every decision evaluable — not just “it worked in the demo.”

The dirty secret? The teams winning in 2026 aren’t the ones moving fastest. They’re the ones who refused to accumulate invisible debt.

[Klydone @klydone]

You hired contractors to move faster.
Now your best engineer spends half her week explaining the codebase to people who leave in 90 days.

That’s not acceleration.
That’s a slow leak.

How does your team actually handle contractor offboarding in practice?

#TechLeadership
#EngineeringManagement
#Startup

[Klydone @klydone]

No-code saved us from engineers.

Then we got:
• 14 broken Zapier flows
• 3 tools nobody understood
• A sales ops manager secretly rewriting everything in Python at 2am

Silent failures don’t show up in dashboards.

They show up in lost deals.

Who actually owns your automation when it breaks at 11pm?

Drop your horror stories below 👇

#RevOps #NoCode #SalesOps

[Klydone @klydone]

Here’s a lightweight shutdown plan you can start using today:

1. Owner defined at creation (not “the team” — a real person)
2. Purpose + dependencies documented
3. Expiration or review date set (even if it’s 6 months)
4. Simple cleanup steps written down (or automated)
5. Monthly 15-min audit of anything without an owner

That’s it.

Want the one-page template we use internally? Reply “template” and I’ll send it.

[Klydone @klydone]

Cloud sprawl rarely starts with bad engineering.

It starts with unclear ownership.

A queue. A cache. A “temporary” service.

Six months later, nobody knows what can be safely removed.

Our rule: no launch without a shutdown plan.

Drop your rule below 👇

#FinOps #CloudSprawl #PlatformEngineering #CloudCost

[Klydone @klydone]

Most teams throw tooling at cloud sprawl.

They buy cost dashboards, tagging policies, and FinOps platforms.

But tooling without clear ownership is just expensive theater.

When no one is explicitly responsible for a resource, even the best tools get ignored.

Ownership isn’t a tag. It’s accountability.

Without it, “we have visibility” becomes “we have a very expensive list of things we’re not fixing.”

[Klydone @klydone]

Cloud sprawl rarely starts with bad engineering.

It starts with unclear ownership.

A queue. A cache. A “temporary” service.

Six months later, nobody knows what can be safely removed.

Our rule: no launch without a shutdown plan.

Drop your rule below 👇

#FinOps #CloudSprawl #PlatformEngineering #CloudCost

[Klydone @klydone]

Your AI agent aced every benchmark.

Then a real user showed up tired, distracted, vague, and typed:

“uhh can you do the thing from before?”

Everything broke.

Not because the model was bad.
Because the testing environment was unrealistically clean.
Most AI systems are evaluated against structured prompts, ideal flows, and predictable behavior.

Real users do not behave like benchmark datasets.

They:

change context halfway through

forget what they asked earlier
use unclear language
contradict themselves
expect memory without precision
abandon flows mid-task
The real production risk is not model intelligence.

It is the gap between controlled evaluation and messy human behavior.

How is your team capturing failure patterns before they become support tickets?

[Klydone @klydone]

Hired 3 devs fast.

Six months later the senior team is rewriting half the codebase.

That is the real invoice for cheap staff augmentation.

The hourly rate looked fine in the budget meeting. It never survives the post-mortem.

What do you wish you had evaluated before signing?

[Klydone @klydone]

Your best engineers aren't slow.

They're spending Tuesday debugging why the environment works on one machine and not another instead of building product.

"Works on my machine" has probably burned more engineering hours than most outages.

What's one backend task your team still runs every week that nobody fully trusts?

[Klydone @klydone]

A surprising amount of “scaling” is just expensive avoidance of root-cause analysis.

More Kubernetes nodes.
More replicas.
More caching.
More infrastructure.

Meanwhile one unindexed query is holding the entire system hostage.

Good engineering is not adding capacity blindly.
It is identifying the real constraint.

What is the most expensive bottleneck your team misdiagnosed?

[Klydone @klydone]

The best AI support agents do less than you think.

We reduced support tickets by 60% in 90 days.

But the breakthrough was not the model.

It was deciding what the agent should never answer.

AI could handle:
- repeat FAQs
- account setup
- workflow guidance
- basic troubleshooting

AI had to escalate:
- billing disputes
- legal questions
- security issues
- angry customers
- low-confidence answers

That was the unlock.

AI resolves the obvious.
Humans handle the risky.

What is one support question your team still answers every week?

[Klydone @klydone]

A contractor shipping your feature is fine.

A contractor becoming the only person who understands your auth system is not.

That is not “moving fast.”

That is importing key-person risk into your architecture.

Which system in your stack could only an outsider explain at 2am?

[Klydone @klydone]

A contractor shipping your feature is fine.

A contractor becoming the only person who understands your auth system is not.

That is not “moving fast.”

That is importing key-person risk into your architecture.

Which system in your stack could only an outsider explain at 2am?