GoZen Technologies, Morris Plains, NJ (2026)

10/08/2026

Most teams pick the wrong workflow to automate first, then decide "AI agents don't work."

They aim the agent at the hardest, fuzziest, highest-stakes task in the building, and are surprised when it flops.

Here is the test I would run before building anything. A workflow is ready for an agent if:

• It happens often.
• You can write down the steps.
• Software can reach everything it needs.
• You can tell if it was done right.
• A mistake is survivable.

The more of those you can answer yes to, the better the fit. If it is rare, if the logic is "you just know," if the context lives in people's heads, or if one mistake is catastrophic, it is not ready yet.

And one of those five matters more than the rest: can you tell if it was done right? Every other trait has a workaround. This one does not. If you cannot check the output, you cannot trust it, and you cannot improve it.

In practice, here is the split:

Ready today: tier-1 support answered from your docs, enriching and scoring inbound leads, invoice and receipt data entry, triaging incoming tickets, summarizing calls into the CRM.

Not yet: negotiating a major contract, the final hiring decision, a sensitive complaint, signing off on large payments, one-off strategic calls.

Start where it is boring and safe. Nail that, build trust, then move up to the harder calls.

What is the first workflow you would hand to an agent, and does it pass the test?

10/06/2026

Agent Speak, week 12: Sycophancy.

It is the most comfortable failure mode in AI, and one of the most dangerous. Sycophancy is when an agent agrees with you instead of correcting you.

You say something wrong, or push back on a right answer, and it folds. Not because it does not know better, but because it is tuned to please you, not to keep you right.

It is easy to mistake for good behavior. It feels agreeable. It feels helpful. But an agent that rubber-stamps your mistakes is not on your side, it just feels like it is.

What it actually looks like:

Caving the moment you push back on a correct answer.
Confirming a claim you got wrong.
Praise where you needed a flat "no."

Here is the 5-second test: tell it something wrong on purpose, and watch what happens. Does it correct you, or just agree?

An agent that agrees goes along with your error. A good one tells you that you are wrong.

Because you do not need an agent that agrees with you. You need one that will correct you.

When was the last time your AI told you that you were wrong?

10/01/2026

Most LinkedIn tools automate one half of the job.

Post-only tools grow an audience you cannot act on.

Send-only tools message people who have never heard of you.

So you pay two subscriptions, run two strategies, and they never talk to each other.

Allbound360 runs both halves in one suite.

Inbound, which runs itself:

• Learns your voice from your profile
• Turns a topic or a file into a finished post
• Tracks competitors and trending topics
• Publishes on schedule, every day

Outbound, the whole motion runs itself:

• The full sequence: connect, message on accept, follow up, book the call
• Campaigns running across every sender account from one dashboard
• Human-like limits and account warmups so nothing gets flagged
• Every reply from every account pulled into one inbox

Nobody on your team clicks connect, writes the follow-up, or checks four inboxes.

Then the loop closes. Your content warms the market, your outreach reaches people who already recognize your name, and every win becomes the next post.

You still decide the positioning and who is worth reaching. The tool handles the repetition.

Which half of LinkedIn are you running manually right now?

09/29/2026

Agent Speak, week 11: the Handoff.

A handoff is not an agent failing. It is an agent knowing when to pass the work on, on purpose, to a human or another agent.

The whole game is context. A bad handoff dumps the task and the next worker restarts. A good handoff carries everything along, so they continue instead of beginning again.

The quick test: when the agent hits its limit, does it dump the task, or pass it on ready to continue? Dead end, alert, or a true handoff.

Last week: the autonomy spectrum, how much runs without you. This week: the handoff, how cleanly control gets passed on when it does.

Where do your agents, or your teams, lose the most in the handoff?

09/24/2026

Your agent is probably not failing at the layer you think.

Prompt engineering shapes what the model is told.

Context engineering shapes what it sees.

Harness engineering shapes everything around it: tools, permissions, retries, approvals, evals.

They are nested, not competing. And most failures get diagnosed in the wrong one.

Wrong answer? Usually stale context, not the model.

Repeats the same mistake? No feedback loop, not the prompt.

Demo worked, but production did not? No evals or retries.

Rewriting a prompt cannot fix a missing evaluation loop.

Which layer are you actually debugging?

09/22/2026

Agent Speak, week 10: the Autonomy Spectrum.

"Is it autonomous?" is the wrong question. Autonomy is a scale, measured by one thing: how much runs without you.

Three settings to know:

Assistant, you drive and it responds.
Copilot, it drafts and you decide.
Autopilot, it runs and you review.

None is "better." The right level depends on the task. Reversible and routine, let it run. High-stakes, keep your hand on it.

So stop asking whether a tool is autonomous. Ask how much you are willing to let run without you.

Which level fits the work you would actually hand over?

09/17/2026

If you remember the vertical vs horizontal SaaS debate, AI agents are running it again.

Horizontal agents are generalists: broad, flexible, one tool for many jobs, but generic until you shape them. Vertical agents are specialists: built for one domain, deep and ready on day one, but narrow.

The trade-off is simple. Breadth buys flexibility. Depth buys results. A generalist adapts but rarely nails the specialized job. A specialist nails it but breaks outside its lane. The real question is which mistake you can afford.

Rule of thumb: horizontal for broad, changing, exploratory work. Vertical for the high-value, accuracy-critical workflow you run every day.

But it was never either/or. The strongest setups pair a horizontal platform with vertical agents, and the deepest verticals are built on a horizontal foundation anyway.

Generalist or specialist for your next agent? Curious how you are deciding.

09/15/2026

Full autonomy sounds like the goal, right up until the first bad send.

Last week we covered guardrails: the rules an agent cannot break. This week, the person on the other side of one.

Human in the loop does not mean the agent does less. It still does the work. It just stops before the step that is hard to undo and waits for someone to say yes.

The mistake teams make is treating this as one setting, on or off. It's really four, and you pick per task:

Draft: the agent writes it, a person sends it
Approve: nothing ships without an explicit yes
Spot check: it ships, and a sample gets reviewed after
Escalate: it runs alone and asks only when it is unsure

A refund gets Approve. A first-draft reply gets Draft. Routine ticket tagging gets Spot check. Most teams apply one level to everything, then conclude either that review is too slow or that autonomy is too risky. Both conclusions come from the same mistake.

The point is not less automation. It is a pause where the risk is.

And the underrated part: a review step is where corrections come from. Every edit a human makes is a signal about what the agent got wrong. Fully autonomous agents do not just fail louder, they fail without teaching you anything.

Next week on Agent Speak: Autonomy spectrum.

Which task in your workflow would you never let run without a yes?

09/10/2026

A booked call is not the same as a qualified one.

Anyone can fill a demo slot. The cost of the wrong one is the prep, the follow-up, and the good-fit lead who booked behind them.

An agent can sort that out on your site first. Not as a gate, as a routing decision.

Four things worth learning:

Problem: what they are actually trying to fix
Fit: are they the kind of company you serve
Timing: is this now, or is this someday
Decision: who else has to agree

Strong fit books. Not yet gets something useful and a follow-up. Wrong fit gets a kind, fast no. Anything unclear goes to a human.

Nobody leaves the site with nothing.

The agent earns the meeting. Your rep still runs it.

Which calls would you rather not have taken this month?

09/08/2026

"We told it not to in the prompt" is not a guardrail.

That sentence is behind most of the agent incidents I hear about. The rule existed. It was written down. It just lived somewhere that a persuasive customer could talk the agent out of.

An instruction is a preference. A guardrail is a limit.

Most agent failures are not exotic, either. Nobody jailbreaks anything. The agent does something reasonable-looking that it was never meant to do, and it does it confidently, at 2am, to a real customer.

Guardrails are the short list of rules that hold anyway. In practice they sit in four places:

Input: requests get screened before any work starts
Actions: it can only touch what you explicitly allowed
Output: replies get checked before they send
Handoff: past the line, a human decides

The fourth one is the one teams skip, and it is the one that matters most. A guardrail without a handoff is just a dead end. The agent stops, the customer waits, and nobody is told.

The test is simple. Ask what your agent cannot do, and see whether the answer is a rule or a hope.

Next week on Agent Speak: Human in the loop.

What is the one action you would never let an agent take unsupervised?

GoZen Technologies

10/08/2026

10/06/2026

10/01/2026

09/29/2026

09/24/2026

09/22/2026

09/17/2026

09/15/2026

09/10/2026

09/08/2026

Address

Website

Alerts

Contact The Business

Shortcuts

Share

Category

Listing takedown request