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Mark Johnson

@markjohnsonit.bsky.social
352 followers 714 following 221 posts

Helping Federal orgs get more from emerging tech. Husband, father, retired Navy pilot. Databricks employee, but all opinions only mine.

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Mark Johnson @markjohnsonit.bsky.social · 19/08/2026
My recent job transition has sharpened my perspective on what AI has accelerated in the sales process versus what hasn’t fundamentally changed. Some leaders assume AI will replace frontline sellers, but top sellers and smart tools complement each other. www.jeffbounds.com/insights/ai-...
jeffbounds.com
Sales Leadership, GTM Strategy & Revenue Growth | Jeff Bounds
Jeff Bounds advises growth-stage founders and CEOs on breaking revenue plateaus through sales strategy, GTM execution, and structural revenue system design. Nashville-based, worldwide reach.
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Mark Johnson @markjohnsonit.bsky.social · 07/08/2026
Every AI demo happens in a cleaner environment than the average enterprise. That's why deployment is so much harder than the demo. Models are improving quickly. Untangling years of systems, processes, and data takes much longer.
cio.com
OpenAI Presence raises new questions about enterprise automation and jobs
OpenAI says Presence resolved 75% of inbound support issues in its own deployment, but analysts say fragmented enterprise systems could limit automation, with slower hiring more likely than immediate job cuts.
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Mark Johnson @markjohnsonit.bsky.social · 31/07/2026
The recent breaches committed by AI models from OpenAI and Anthropic demonstrate why common standards and testing programs are important. A neutral, trusted body needs to be in place to oversee these models. www.cnbc.com/2026/07/14/g...
cnbc.com
Google DeepMind chief Demis Hassabis calls for U.S. to spearhead AI standards body
Tech giant's AI boss said "urgent action" was needed as AI capabilities advanced.
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Mark Johnson @markjohnsonit.bsky.social · 28/07/2026
One thing I respect: admitting reality. Zuck said Meta's development using AI agents has been slower than expected. That's refreshing. Companies learn faster when leaders are honest about what's working, what's not, and what needs to change.
techcrunch.com
Mark Zuckerberg tells staff that AI agents haven't progressed as quickly as he'd hoped | TechCrunch
At an internal meeting, the Meta CEO reportedly said that AI development efforts were not moving as quickly as anticipated.
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Mark Johnson @markjohnsonit.bsky.social · 24/07/2026
I've always told federal clients: I can fix a lot of technology problems. I can't fix your policy problems. AI is exposing how many policies were written for a different era. If we want AI to deliver actual value, the policies need to evolve alongside the technology.
meritalk.com
Federal CIO Reflects on Tenure, Calls for Congressional Tech Reforms
As he prepares to leave government, Greg Barbaccia says cultural change among agency CIOs is his biggest accomplishment – but warns outdated laws will continue to slow modernization without congressional action.
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Mark Johnson @markjohnsonit.bsky.social · 22/07/2026
AI deployment fails when we ignore the human element. One tip for federal leaders: Fix the "role friction." Clearly define where the machine's work ends and human authority begins. #GovTech
blog.stackademic.com
Your Coworker Is an Algorithm, And That’s Not the Problem You Think It Is
How AI is quietly reshaping every desk, operating room, and boardroom and why the humans who learn to work with it are already winning
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Mark Johnson @markjohnsonit.bsky.social · 21/07/2026
AI agents create a new management skill. Most leaders know how to hire, coach, & organize. Far fewer have experience deciding what work belongs with a person, what belongs with an AI agent, and how those two work together. Figuring it out first will give you an advantage that's difficult to copy.
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Mark Johnson @markjohnsonit.bsky.social · 20/07/2026
AI adoption isn't a tech problem; it's a people problem. Two ways federal IT leaders can win: 1. Map employee readiness archetypes. 2. Build trust, not just tools. #AIGov
weforum.org
The 5 faces of human readiness for AI adoption – and how to work with them
Recent research reveals five distinct postures among employees regarding AI's potential and their openness to adopting it. Here's how business can safeguard the human factor
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Mark Johnson @markjohnsonit.bsky.social · 17/07/2026
During rapid change, teams rarely run out of ideas—they lose alignment. Before discussing tactics, reconnect on purpose: What are we trying to achieve? What hasn't changed? What tradeoffs matter? Clear answers create focus, and focused teams execute faster.
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Mark Johnson @markjohnsonit.bsky.social · 13/07/2026
91% of respondents said they're creating new AI budgets rather than cutting existing software spend. If that trend holds, AI isn't following the adoption pattern most enterprise software did. That suggests we're still early.
businessinsider.com
This new research challenges nearly every big AI narrative of 2026
RBC's latest CIO survey finds no AI token panic, no SaaSpocalypse, and surging enterprise AI spending, led by OpenAI.
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Mark Johnson @markjohnsonit.bsky.social · 08/07/2026
I think data management will be one of the defining leadership challenges of the AI era. Two teams can look at the same business & produce different numbers because they pull from different sources. When those inconsistencies feed AI systems that people rely on for major decisions, that's an issue.
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Mark Johnson @markjohnsonit.bsky.social · 08/07/2026
Watching Kellie's organizing work has reinforced something a core belief: people underestimate the value of structure. Disorganization creates friction. Time gets spent looking for things, revisiting decisions, and navigating confusion. Good systems free people to focus on what actually matters.
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Mark Johnson @markjohnsonit.bsky.social · 02/07/2026
A few years ago, it would have been strange for an AI conversation to focus on electricity. Today, data centers are buying power developers as they struggle to meet demand. I didn't expect one of the more interesting AI stories of 2026 to involve power companies, but here we are.
A few years ago, it would have been strange for an AI conversation to focus on electricity. Today, data centers are buying power developers as they struggle to meet demand.

I didn't expect one of the more interesting AI stories of 2026 to involve power companies, but here we are.
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Mark Johnson @markjohnsonit.bsky.social · 22/06/2026
The DOD's prototyping is impressive, but the real challenge is getting to production. I think we need more partnerships between innovators and established DoW providers. What holds us back? www.washingtontechnology.com/contracts/20...
washingtontechnology.com
DOD excels at prototyping. Getting to production is another story.
Acquisition reform may be the bridge, but the paths from prototype to funded program remains unclear.
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Mark Johnson @markjohnsonit.bsky.social · 15/06/2026
On my way to #DataSISummit in SF! If you're going, let's get together and talk Federal IT Data and AI solutions!
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Mark Johnson @markjohnsonit.bsky.social · 12/06/2026
Organizations spend so much energy on models & little on how they house their data or who can access it. That's backwards. If you don't understand your data's chain of custody, it's at risk. www.reuters.com/legal/legalindustry…
Organizations spend so much energy on models & little on how they house their data or who can access it. That's backwards.

If you don't understand your data's chain of custody, it's at risk.

https://www.reuters.com/legal/legalindustry/cloud-data-centers-your-trade-secrets--pracin-2026-06-01/
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Mark Johnson @markjohnsonit.bsky.social · 08/06/2026
During a trip to Japan last year, I learned about "hansei": reflecting on a process even when it succeeds. Most teams review failures. They should review wins too. Success can validate good decisions, but can also hide weak assumptions. Reflection must be a habit instead of a response to a problem.
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Mark Johnson @markjohnsonit.bsky.social · 07/06/2026
Patience is an underrated career skill. Many bad career decisions are made in a rush to end uncertainty. Ambiguity is uncomfortable, so people force the wrong opportunity. Most transitions have an awkward middle period. It can feel like stagnation. Usually, it’s just recalibration.
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Mark Johnson @markjohnsonit.bsky.social · 05/06/2026
The DoD's AI Acceleration Strategy is directionally right and the $30B budget request for infrastructure is also good. Now let's work together to show how to securely share data so everyone who needs it, has it!
federalnewsnetwork.com
DoD AI Acceleration Strategy marks move toward real-time insight: Here’s what agencies should do next | Federal News Network
As the focus shifts from testing AI in research labs to real-world use, agencies must implement it responsibly through continued testing.
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Mark Johnson @markjohnsonit.bsky.social · 04/06/2026
DoD's contested logistics sprint includes an AI tool to help commanders make real-time decisions. The hard part: connecting data across commands. AI is as good as it's data. nationaldefensemagazine.org/articles/2026/5/11/pentagon-sprints-to-field-systems-to-sustain-troops-in-denied-environments
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Mark Johnson @markjohnsonit.bsky.social · 03/06/2026
$29.5 billion to centralize & scale DoD's AI computing infrastructure is a huge investment. I'll be interested in seeing what gets ingested into all that compute. $30 billion of infrastructure running on poorly governed data might produce faster decisions, but they won't be better ones.
defensescoop.com
DOD wants nearly $30 billion to modernize its AI supercomputing arsenal in fiscal 2027
“The White House’s AI Action Plan, released last year, outlines the importance of establishing robust AI infrastructure,” an official said.
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Mark Johnson @markjohnsonit.bsky.social · 31/05/2026
A miscoded field in one program office is a minor annoyance. The same field ingested into an enterprise AI system across twelve offices informs four months of award decisions before anyone notices. Scale only buries data problems deeper and spreads them wider.
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Mark Johnson @markjohnsonit.bsky.social · 29/05/2026
894 million tokens per day in agentic workflows during Operation Epic Fury. Compute bottleneck is a serious concern. But I'd push back gently on where the focus should actually be. The data governance layer underneath those workflows is the constraint getting a fraction of the attention it needs.
defensescoop.com
DOD planning to address compute ‘bottleneck’ that could hinder AI proliferation
Compute is currently a top concern, Pentagon Chief Digital and AI Officer Cameron Stanley said at an AI expo.
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Mark Johnson @markjohnsonit.bsky.social · 26/05/2026
Stop by the @databricksinc.bsky.social table at the AFCEA Bethesda Health IT Summit this week and let's talk about enabling the workforce with better data and analytics to improve health outcomes!
Databricks team photo
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Mark Johnson @markjohnsonit.bsky.social · 22/05/2026
Eight AI vendors now have agreements to deploy on DoD's classified networks. Buried in the announcement: it's not clear how the department plans to use them. Access and readiness to deploy responsibly are different problems. Adding vendors doesn't solve the second one.
federalnewsnetwork.com
DoD strikes deals with major tech firms to deploy AI on classified networks | Federal News Network
It's not clear how DoD will use new AI tools, but officials said the effort will enable capabilities across warfighting, intelligence and enterprise operations.
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Mark Johnson @markjohnsonit.bsky.social · 20/05/2026
The Army automated 150+ workflows with CDAO's Wingman & got back 687,000 work hours & $37M in cost avoidance from operational use. But federal data ownership is murky & automation will amplify problems if the right data governance layer is not in place.
defensescoop.com
A first look at CDAO’s new ‘Wingman’ work to enable custom, AI digital assistants across DOD
An official involved said the goal isn’t to replace humans with AI, but to free up their time for critical thinking and higher-value work.
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Mark Johnson @markjohnsonit.bsky.social · 19/05/2026
Everyone has AI tools. Almost nobody answers the most important questions before deploying them: which tools are trusted for which decisions, and who owns an output when it's wrong. It's a governance gap that exists long before the tool goes live. It just becomes visible six months later.
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Mark Johnson @markjohnsonit.bsky.social · 13/05/2026
DoD has decades of data across every domain. The harder question is whether the workforce can tell you which sources are authoritative and trustworthy enough to act on. That's an issue with data maturity, and policy reforms alone won't solve it.
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Mark Johnson @markjohnsonit.bsky.social · 07/05/2026
When direction changes, the instinct is to get straight to solutions. Before that, the team needs to understand why the work still matters and how the new direction connects to what they were already doing. Skip that conversation and the execution always suffers.
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Mark Johnson @markjohnsonit.bsky.social · 06/05/2026
Looking forward to the AFCEA DC luncheon on May 13th on operationalizing agentic AI for DoW. With agentic AI, the system takes actions autonomously. A bad output can execute a bad decision before anyone reviews it. That's a governance problem & I'm curious how DoW CIOs are thinking about that.
dc.afceachapters.org
Luncheon Series - AFCEA DC
2025-2026 AFCEA DC Luncheon Series Army Navy Country Club | 1700 Army Navy Drive, Arlington, VA 22202 Sponsor the AFCEA […]
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Mark Johnson @markjohnsonit.bsky.social · 30/04/2026
Agencies are losing 25–35% of their statistical staff while standing up AI at scale. To be successful, we must invest in the tools that ingest, prep, and govern the data as much as the flashy AI tools that use it.
federalnewsnetwork.com
The data challenge impacting federal AI adoption | Federal News Network
Data readiness is the true starting point in the race toward AI adoption progress, and mission success depends on it.
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Mark Johnson @markjohnsonit.bsky.social · 21/04/2026
AI pilots run on data someone prepared specifically for them. Production runs on data the way it actually exists: pulled from different systems, inconsistent, and nobody owns it. And that's why most pilots don't survive the transition.
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Mark Johnson @markjohnsonit.bsky.social · 20/04/2026
DoD has no shortage of AI pilots. What it has a shortage of is deployments that made it to production and stayed there. The data strategy, lineage, and governance underneath are what determine which pilots survive the transition.
federalnewsnetwork.com
DoD Modernization Exchange 2026: Microsoft’s Vassili Patrikis on scaling AI adoption | Federal News Network
Organizations with successful AI projects tend to think big but start small, Microsoft AI expert says.
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Mark Johnson @markjohnsonit.bsky.social · 16/04/2026
Great article that captures the "train like you fight" mantra for data: "share so you can fight better." The question is, do we have the overall governance in place to get the right data to the right person at the right time?
federalnewsnetwork.com
DoD Modernization Exchange 2026: Salesforce’s Allan Day on breaking down data silos to create decision advantage | Federal News Network
Trust and transparency in data are a must to ensure the Pentagon deploys AI capabilities that deliver joint force strategic value, the Salesforce expert says.
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Mark Johnson @markjohnsonit.bsky.social · 15/04/2026
AI outputs look authoritative. Agents present data with confidence even if it's a total fabrication. Confidence in an AI output should be proportional to confidence in the data behind it. That means knowing where it came from and when it was last validated. The interface doesn't tell you that.
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Mark Johnson @markjohnsonit.bsky.social · 09/04/2026
Democratizing data is a good instinct. But if you don't have strong governance over the entire data pipeline, nobody can trace where a number came from. When a senior leader asks, you need to be able to answer that--and prove it.
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Mark Johnson @markjohnsonit.bsky.social · 07/04/2026
The Pentagon's new AI strategy mandates data sharing across classification levels, but we know that significantly increases cyber risk. How are you putting the governance in place to securely share data? Policy directives alone won't fix it.
federalnewsnetwork.com
Pentagon’s AI strategy features focus on data sharing | Federal News Network
The Pentagon’s new artificial intelligence strategy has many facets, including a major emphasis on sharing data to advance “AI exploitation and mission advantage.” In the Jan. 9 memo laying out the…
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Mark Johnson @markjohnsonit.bsky.social · 06/04/2026
Knowing how sales reps and tech people are motivated differently isn't the hard part. Building the structure around it is. Most leaders know the distinction. Few actually restructure around it.
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Mark Johnson @markjohnsonit.bsky.social · 03/04/2026
People ask me how they can trust their AI. If their data is inconsistent or siloed, they can't. For federal, the stakes are high, & you can't blame mistakes on the AI. That's not how accountability works. So always ask: can you trace where an output came from?
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Mark Johnson @markjohnsonit.bsky.social · 02/04/2026
The government has decades of data across every domain & most of it wasn't built to be machine-readable, yet we ask AI to make sense of it anyway. Before you can get reliable AI output, you have to do the unglamorous work of training the models on relevant data. This bill is a step toward that.
budd.senate.gov
Budd, Kim Introduce Bipartisan Bill Opening Government Data Sets to Better Train American AI Models - U.S. Senator Ted Budd
The Artificial Intelligence Ready Data Act would create a modern federal approach to opening government data assets to train and develop stronger American artificial intelligence (AI) models.
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Mark Johnson @markjohnsonit.bsky.social · 30/03/2026
In the Navy, we said: "garbage in, garbage out." Bad intel = bad outcomes, no matter how advanced the tech. The same logic applies to AI in government. Everyone's focused on the model when we should be talking about the data feeding it. If the data's bad, the model won't matter.
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Mark Johnson @markjohnsonit.bsky.social · 24/03/2026
AI increases output speed, but decision quality still depends on data latency, freshness, and validation cycles. When those lag, decisions move on outdated inputs. Speed amplifies whatever sits beneath it. If data pipelines fall behind, misalignment spreads just as quickly as progress.
AI increases output speed, but decision quality still depends on data latency, freshness, and validation cycles. When those lag, decisions move on outdated inputs.

Speed amplifies whatever sits beneath it. If data pipelines fall behind, misalignment spreads just as quickly as progress.
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Mark Johnson @markjohnsonit.bsky.social · 23/03/2026
Sales reps tend to perform best when they can go deep on a single customer. Technical roles usually look to build skills with a specific capability, so need to work across clients. If you treat them the same, performance suffers, but if incentives reflect how each group operates, results improve.
Sales reps tend to perform best when they can go deep on a single customer. Technical roles usually look to build skills with a specific capability, so need to work across clients.

If you treat them the same, performance suffers, but if incentives reflect how each group operates, results improve.
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Mark Johnson @markjohnsonit.bsky.social · 20/03/2026
Hesitation carries cost. Work stalls and responsibility diffuses. My time in the Navy taught me early on to gather inputs, assess risk, make the call, & own the outcome. Real leadership shows up when someone accepts responsibility & moves the work forward.
Hesitation carries cost. Work stalls and responsibility diffuses. My time in the Navy taught me early on to gather inputs, assess risk, make the call, & own the outcome.

Real leadership shows up when someone accepts responsibility & moves the work forward.
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Mark Johnson @markjohnsonit.bsky.social · 19/03/2026
Compensation matters. Perspective matters more. Time spent chasing the last dollar carries an opportunity cost and energy invested in building customer relationships can change the entire scoreboard. Leaders help people see that difference and build for long-term growth.
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Mark Johnson @markjohnsonit.bsky.social · 18/03/2026
AI concentrates responsibility. As adoption accelerates, data discipline determines outcomes. Incomplete or poorly governed data scales risk. Data quality, access controls, and validation require clear ownership. Before expanding capability, examine the data environment behind it.
AI concentrates responsibility. As adoption accelerates, data discipline determines outcomes. Incomplete or poorly governed data scales risk. Data quality, access controls, and validation require clear ownership. Before expanding capability, examine the data environment behind it.
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Mark Johnson @markjohnsonit.bsky.social · 10/03/2026
In the cockpit, the plan rarely survived weather or traffic. You adjusted inputs, recalculated fuel, confirmed data, & kept flying. Leadership works the same way. When guidance shifts, process the new information & revise the plan. Adaptability is decision quality under change.
forbes.com
Why Adaptability, Not Resilience, Is Today’s Key Leadership Skill
Leadership consultant Mike James Ross reveals why resilience has reached its limit—and why CEOs must build unprecedented adaptability to stay competitive.
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Mark Johnson @markjohnsonit.bsky.social · 09/03/2026
I was asked why a sales org wasn’t seeing the behaviors leaders wanted, despite incentives. Truth is, structure drives behavior. Pay a rep on one account & they’ll go deep there. Put tech on a pooled plan & they’ll specialize across customers. People move toward how they’re measured & rewarded.
I was asked why a sales org wasn’t seeing the behaviors leaders wanted, despite incentives. Truth is, structure drives behavior. Pay a rep on one account & they’ll go deep there. Put tech on a pooled plan & they’ll specialize across customers. People move toward how they’re measured & rewarded.
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Mark Johnson @markjohnsonit.bsky.social · 08/03/2026
During turbulent periods, stability becomes the outcome. Leaders can’t remove volatility. The measure is whether the team keeps operating with direction and confidence. Stability comes from clear decisions, defined ownership, and steady communication when variables move.
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Mark Johnson @markjohnsonit.bsky.social · 02/03/2026
Guidance doesn’t always arrive on time. Leaders still owe their teams movement. Define what’s known, choose a near-term path, document assumptions, and assign ownership. When updated direction lands, adapt. Until then, lead with the best judgment available and stay accountable.
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