Hard Skill Exchange

Founder & CEO

CEO @ Hard Skill Exchange | The Stock Market of Skills

Julia is the CEO and Founder of Hard Skill Exchange, the stock market of skills for go-to-market innovation. 

A CMO by 30, she advanced through the Salesforce ecosystem and launched a “Product Hunt for GTM methodologies” as an intrapreneur, inspiring the creation of HSE.

Today, she leads a network of 20,000+ executives, operators, analysts, and VCs and hosts AI Summits and AI Practice Sessions focused on operationalizing AI-native GTM. 

She holds a master’s degree in linguistics.

Freeing from excessive expectations leads to the strength of the result.

We are finally getting rid of the nonsense that AI will escape control and begin to ‘rule people.’

What matters is the cycle of innovation.

Clay Christensen showed that disruption comes from new architectures that emerge once technology overshoots what customers can use. Gartner’s Hype Cycle mirrors the same pattern: inflated expectations, decline, and then durable progress.

AI sits at its peak today. At this stage, something disruptive must appear, explosive in form, aggressive in redefining value. Those who focus only on the peak risk collapsing with it. Those who examine the processes within the innovation itself will see where the real trajectory begins.

In GTM, the next trajectory is 'agent swarms' – polyfunctional agents coordinating across sales, marketing, and customer success. Workflows that once demanded entire teams now run in parallel and improve continuously.

The linear funnel gives way to adaptive loops: market signals sensed and acted upon instantly, decisions distributed across agents, and execution powered by AI. The human remains central, as orchestrator of a system that learns, aligns, and scales with every cycle.

The emerging Jobs to Be Done of agent swarms:

• Govern distributed agent swarms (Vanta, Drata, Collibra, Guardrails AI, Usercentrics)

• Detect and prioritize buyer activity (Metadata, Warmly, Mutiny, 6sense, Octave)

• Embed agents in buyer workflows (WINN.AI, Navu, Scrunch AI, Cluely, Profound)

• Orchestrate polyagent GTM loops (Momentum.io, Boomi, revlogic, Workato, Tray.ai)

• Redesign revenue orgs with agents (Alysio, Nooks, ZoomInfo, Artisan, SalesAi)

• Monetize agent-driven output (RevSure AI, Paid, Ramp, VAYOU, Equals)

• Retain customers with adaptive agents (Hook, Gainsight, Planhat, Clozd, Forethought)

• Build moats with swarm intelligence (Zapier, Snowflake, HG Insights, Pinecone, LangChain)

> On October 28, at the AI Practice Sessions, leading B2B executives and operators will show how agent swarms are being deployed across GTM.
Attend free/ virtual: https://lnkd.in/d9PB57Zx 

#agentswarms #aipracticesessions

Julia Nimchinski

What if distribution is not the channel you optimize after product–market fit, but the proof of it?

Last week, 2,500+ CXOs, operators, VCs, analysts, and founders joined the Hard Skill Exchange Agentic Distribution Summit.

In SaaS, distribution has often been treated as a channel to optimize: add another sales rep, expand the ad budget, tune the funnel. With AI, the temptation is similar – add an agent, connect an API, and expect scale.

The summit reframed it: distribution is not parallel to product–market fit. Distribution is product–market fit. Retention validates product value; distribution validates whether product, market need, and reach align.

AI changes the pace. Execution cycles compress, ICPs can refresh daily instead of quarterly, and seller face time with customers could rise from ~25% to 80–90%. Yet the constraint remains the same: alignment between product, buyer, and the mechanism of reach.

Over 35 fireside chats, demos, and roundtables, leaders mapped the problems shaping agentic distribution and the shifts AI-native distribution brings to GTM. Each panel left us with metaphors as vectors for solving.

Last week, 2,500+ CXOs, operators, VCs, analysts, and founders joined the Hard Skill Exchange Agentic Distribution Summit. In SaaS, distribution has o

Open article: The Distribution Fit by Julia Nimchinski • 7 min read

“What used to be sequential becomes simultaneous.
Agents compress learning cycles. 
PMF and GTM fit can run in parallel.” 
— Mark Roberge (Co-Founder, Stage 2 Capital, HBS Professor, Founding CRO, HubSpot)

At the Agentic Distribution Summit, I lined up a small library of questions for Mark. We got through… one. ;-) 

Simple prompt:
If you were rewriting The Sales Acceleration Formula today, what new chapter would you add for GTM leaders building with agents?

And then classic Mark moment: the next chapter, the last chapter, and everything in between.

Key points from our fireside chat: 

(1) Parallelized growth
Scaling latency shrinks. Capacity flexes daily. With agents absorbing prep and admin, customer-facing time can expand from ~25% toward ~80%.

(2) Four GTM abstractions
Phase 1: human seller to human buyer, with agent support.
Phase 2: seller is an agent.
Phase 3: buyer is an agent.
Phase 4: selling dissolves into product, finance, and ops as functional boundaries fade.

(3) Near-term operating shifts (12 months)
ICP refreshed continuously. Target accounts statistically optimized. DMU mapping and outreach agent-assisted. Meetings simulated and guided. CRM, forecasting, deal rooms, and scorecards auto-updated. Hiring and performance loops continuous. (Examples: Letter AI for enablement; Momentum.io for forecasting.)

(4) Adoption filters
“10x AI” stories often reflect PLG plus experimentation revenue. Enduring adoption shows up in mission-critical use cases and retention. First-mover advantage is overstated – ~12% win rate vs ~88% for fast followers.

(5) Defensibility at the point of work
Owning the transcript, contract, or invoice matters more than owning the database. Vertical AI firms gain strength in regulated sectors where compliance and peer adoption drive selection.

(6) B2B buying rewired
When buyer agents evaluate seller agents, decisions shift from relationships to fit. Selection favors accuracy, ROI, and proof of success. Trust by steak dinner fades; trust by data takes its place.

(7) Operator mandate
Build AI-run organizations vs AI-adjacent features. CAC can decline, but orchestration costs appear. Readiness to scale is measured by the ability to run PMF, GTM fit, and enablement in parallel.

Full recording: https://lnkd.in/d2RmchmU

Shameless plug "Science of Scaling" - pre-order Mark's new book: https://lnkd.in/dQCZDMGQ

Gainsight Salesloft Momentum.io Metadata Amoeba AI Vivun N.Rich Fullcast Dana Consulting (NYC) Meerkat, Inc. Alysio RevSure AI Nooks Averi Salespeak.ai Greaser Consulting HG Insights Qualified ZoomInfo Demandbase Descript Common Room

#agenticdistribution #agenticscaling #ainativegtm

“The IT department of every company is going to be the HR department of AI agents in the future.”

– Jensen Huang, CEO, NVIDIA

That shift is now visible in GTM.

Entire workflows once requiring full teams are beginning to be orchestrated by swarms of polyfunctional AI agents, coordinating across Sales, Marketing, and Customer Success in parallel, continuously improving.

On October 28, we’ll unpack what agent swarms look like in production – how they route intent, embed into buyer workflows, and scale execution loops that align humans and AI.

Agent swarm methods from:
Gainsight, Metadata, Momentum.io, Navu, Hook, WINN.AI, and more.
Lisa Sharapata🌟, Natasha Evans, Maja Voje, Eldad Postan-Koren, Kingston Duffie, Jonathan M K.

10 sessions will cover:
1/ Governing distributed agent swarms
2/ Embedding agents directly in buyer workflows
3/ Redesigning revenue orgs and GTM loops with swarms

Attend free/ virtual: https://lnkd.in/d9PB57Zx

#agentswarms

“Did you ever want to speak with an SDR? 
So why are we taking an AI SDR and amplifying it?”

– Omer Gotlieb (Founder & CEO, Salespeak.ai, Co-Founder, Totango)

A recurring trend at the Agentic Distribution Summit was the misconception that “AI SDRs” will replace human outbound.

The temptation in every wave of technology is to automate the existing model. The real opportunity lies in reconsidering the function from first principles.

Mario Moscatiello (Head of Growth, Airbyte): 
"I don’t believe in AI SDRs. The better path is to turn every SDR into a superhuman. SDR is the hardest job in tech – you’re told no a thousand times a month. AI is good at yes/no decisions. So the opportunity is to ask: what if the SDR role didn’t exist, and how would we reinvent it from scratch? By using AI to remove the repetitive work, we can make SDRs more successful and ultimately increase ROI.”

Watch the full recording: https://lnkd.in/d2RmchmU 

Gainsight Salesloft Momentum.io Metadata Amoeba AI Vivun N.Rich Fullcast Dana Consulting (NYC) Meerkat, Inc. Alysio RevSure AI Nooks Averi Salespeak.ai Greaser Consulting HG Insights Qualified ZoomInfo Demandbase Descript Common Room

#agenticdistribution #agenticgrowth #ainativegtm

The next buyer-seller channel

How are you preparing for a world where your customer’s first conversation is between your agent and theirs?

On the CMO Roundtable at the Agentic Distribution Summit, Carilu Dietrich (CMO, Hypergrowth Advisor, Took Atlassian Public) led a discussion on this shift: agents as buyers, agents as operators, and the inevitability of agent-to-agent conversations.

Data points & trends: 

(1) Agents as buyers
Carilu: distribution has expanded from email, ads, partners, and websites to agents that research, compare options, and in e-commerce place items in carts. In B2B, this moves the first “sales call” upstream from your site.

(2) Higher-intent traffic from AI answers
Marcel Santilli (CEO & Founder, GrowthX AI, Ex-CMO, Deepgram, Scale AI): visitors arriving after 15-20 minutes in LLM answers convert 3-5x higher. Content changes in those answer surfaces can appear within hours vs months.

(3) Agent-to-agent execution with human approval
Tooba Durraze, Ph.D. (Founder & CEO, Amoeba AI): teams request agents to exchange information and trigger actions across platforms while humans approve recommendations.

(4) Autonomous campaign operations
Lisa Sharapata🌟 (VP AI & GTM Strategy, Metadata): parameterized bid agents adjust LinkedIn spend continuously and coordinate with other agents via MCP connectors; teams toggle on or off and set bounds.

(5) Avoid scaling broken work
Omer Gotlieb (Founder & CEO, Salespeak.ai, Co-Founder, Totango): automating legacy SDR patterns floods buyers. The goal is to create an intelligent conversation layer that enhances the experience over increased volume.

(6) Operator leverage without headcount first
Kevin Marasco (CGO, Tebra, Ex-4X CXO, Zenefits, Taleo, HireVue): agents generate battle cards, references, coaching feedback, and call insights, compressing enablement cycles across email, chat, voice, and web.

→ Web experiences bifurcate for humans and for agents, each with different information needs and formats.

→ Qualification evolves toward Agent Qualified Leads as agents complete most early steps; forecasting and attribution models will need revision.

→ Trust becomes an asset: fact-checking, security review, and transparent guardrails are required to sustain adoption and reliability.

Full recording: https://lnkd.in/d2RmchmU

Gainsight Salesloft Momentum.io Metadata Amoeba AI Vivun N.Rich Fullcast Dana Consulting (NYC) Meerkat, Inc. Alysio RevSure AI Nooks Averi Salespeak.ai Greaser Consulting HG Insights Qualified ZoomInfo Demandbase Descript Common Room

#agenticdistribution #agenticmarketing #ainativegtm

Curious if anyone in my network is building or deploying agent swarms? 

Think polyfunctional systems where multiple AI agents coordinate in real-time to route intent, personalize execution, and adaptively align product with market.

We’re seeing the funnel dissolve into adaptive GTM loops, powered by distributed agents running Sales, Marketing, CS, and Ops as a single system. 

E.g. Rox.com 

What's the most cutting-edge use case/tech you've seen?

Open article: Rox | AI-Powered Sales Productivity Platform by rox.com

Rox | AI-Powered Sales Productivity Platform

The next decade of enterprise software will be defined by economics.

If an AI agent performs the same workflows as a human operator, how should it be monetized?

– Per seat, like SaaS
– Per task, like RPA
– Or by Human-Equivalent Value (HEV), a new unit of labor that collapses headcount, productivity, and software into one line item

The implications:
– Margins shift as enterprises replace variable labor costs with fixed agent infrastructure
– Pricing models determine whether agents expand budgets or cannibalize them
– Value capture migrates from workflow efficiency to outcome delivery

At Paid, agents are priced in HEVs – teams saved per month – visible from day one. Buyers hear “a virtual AP clerk saving 15 staff-hours/week” vs “automated invoice parser.” The difference improves understanding, trust, and adoption.

Stanford’s latest survey of 1,500 U.S. workers echoes this: people adopt agents that remove low-leverage work and make their contribution clearer vs systems that overstep.

Design decisions follow a clear matrix:
– High desire / high capability → Deploy
– High desire / low capability → Invest
– Low desire / high capability → Apply selectively
– Low desire / low capability → Defer

Pricing models are evolving in parallel:
– Hybrid (subscription + usage) adoption grew from 27% to 41% in one year
– Outcome-based pricing is gaining traction in AI: tied to completions, resolutions, revenue impact
– Success depends on four variables: consistency, attribution, measurability, and predictability (CAMP)

These shifts are reshaping how software companies price, deliver, and capture value.

At the Agentic Distribution Summit, Manny Medina (Co-Founder & CEO, Paid / Outreach) and Mark Organ (CEO Coach, Categorynauts & Founding CEO Eloqua, Influitive) will break down the new pricing architecture for agent-led GTM.

Session: The Business Model of Agents: Monetizing Human-Equivalent Value
Date: September 17 @9:00am PT 

Attend free/ virtual: https://lnkd.in/d2RmchmU

Gainsight Salesloft Momentum.io Metadata Amoeba AI N.Rich Fullcast Dana Consulting (NYC) Meerkat, Inc. Averi Salespeak.ai RevSure AI

#agenticdistribution #aimonetization #aipricing #agenticbilling

The new AIO (GEO/ AEO) ranking factor is NPS.

Have they even standardized on one acronym: SEO for GPT? 

“If your NPS scores are terrible but you’re running every SEO tactic, you may see short-term gains, until rankings align with reality and you disappear.”
– Eli Schwartz, Product Led SEO

More Eli:

When Google introduced PageRank, it applied an academic model: authority flows through citation. Over time, marketers monetized the loop. Links became tradable. Authority detached from quality.

In the LLM era, search is being re-centered on user satisfaction. Ranking systems are converging with product truth. Advocacy, not backlinks, has become the more reliable measure of authority.

Essence from Eli's fireside chat w/ Kelly Hopping (CMO, Demandbase):

(1) SEO fundamentals persist. Whether queries originate on Google, ChatGPT, or Perplexity, discovery continues to reward clarity of intent and usefulness.

(2) Tactical manipulation is decaying. Algorithms are devaluing keyword density, paid links, and synthetic content in favor of authentic, outcome-aligned experiences.

(3) The mid-funnel is where leverage compounds. AI interfaces now resolve top-funnel questions instantly. Advantage shifts to the point where evaluation and action converge.

(4) NPS is emerging as the new authority signal. Advocacy and satisfaction increasingly determine visibility. Each promoter functions as an organic distribution node.

(5) Attribution must be holistic. Search performance reflects product truth, brand strength, and customer outcomes. Visibility is earned across systems vs isolated within channels.

Full recording: https://lnkd.in/d2RmchmU

Gainsight Salesloft Momentum.io Metadata Amoeba AI Vivun N.Rich Fullcast Dana Consulting (NYC) Meerkat, Inc. Alysio RevSure AI Nooks Averi Salespeak.ai Greaser Consulting HG Insights Qualified ZoomInfo Demandbase Descript Common Room

#agenticdistribution #aio #geo #aeo #seo

A recurring thought lately: what is the function of the human anyway?

Inside legacy workflows – meetings, calls, reviews – the human remains present, but often redundant.

E.g., Do we really need teams trained to repeat 'the perfect pitch' when agents can already generate, test, and optimize it continuously?

What’s wrong with the current state of AI coaching:

(1) The coaching is just training.
It transfers 'techniques' vs thinking; scales conformity vs capability.

(2) The training reflects a pre-AI market reality.
Built on legacy GTM methods, static team structures, and decision cycles that move slower than the market itself.

(3) That agenda produces replaceability.
Teams are being 'trained' to master workflows that AI will soon execute autonomously / won't exist. 

Real AI coaching starts where traditional training ends.
Developing leaders who can design, govern, and scale agentic systems that learn continuously.

We’re building that model in the background and will share more soon.
If you’re a GTM leader interested in shaping this next chapter, DM me.

The 40% agent project failure problem

“In the future, the AE career path will not start as an SDR.”
“In the future, AI will be my entire Sales team.”
“In the future, my SaaS-era sales tools will become irrelevant.”

McKinsey estimates generative AI could add $4.4 trillion annually across industries. Yet Gartner projects that 40% of agentic AI initiatives will be cancelled by 2027 due to weak ROI and immature use cases.

The paradox: 92% of companies plan to increase AI spending, but only 1% call themselves mature in adoption. Employees are already using AI at scale, leaders have yet to catch up.

For CROs, the challenge reduces to three questions:

(1) Which workflows today deliver measurable revenue impact with agents? 
(2) How can CROs design governance and adoption models that protect ROI from being one of the 40% of cancelled projects?
(3) What new performance frameworks and KPIs should replace legacy metrics in a hybrid human–agent environment?

On September 17 at 1pm PT, Matthew D. (CEO, Vivun) will lead a CRO Roundtable 'CRO Strategy in the Agentic Era' with revenue leaders already deploying agents in production:

Allison Grieb, CSO, Paystand
Trevor Jett (Childers), CRO, Vivun
Francis Brero, VP AI, HG Insights
Vinesh V., CRO, Smarsh
Stephen D'Angelo, Partner, Boston Consulting Group (BCG)

This session will cover:
– Sales workflows durable under agent execution
– What gets deprecated as AI embeds across GTM
– Why legacy KPIs mislead in hybrid models
– Governance, trust, and adoption at scale
– New CRO org models and frameworks for sustainable ROI

Format: Q&A, debate, prediction. Real cases. Real failures. Real progress.

Attend free, virtual: https://lnkd.in/dXjE_Vuw
Hard Skill Exchange

Gainsight Salesloft Momentum.io Metadata Amoeba AI Vivun N.Rich Fullcast Dana Consulting (NYC) Meerkat, Inc. Alysio RevSure AI Nooks Averi Salespeak.ai Greaser Consulting HG Insights Qualified ZoomInfo Demandbase Descript Common Room

#agenticdistribution #agenticsales #gtm

Agent overload

“We’re in the agent propagation phase. Every team has built agents for everything, and now the real work begins: determining which ones actually create value.”

– Carilu Dietrich (CMO, Hypergrowth Advisor, Took Atlassian Public)

Every innovation cycle follows the same pattern: expansion, saturation, and rationalization.

In marketing and go-to-market, that rationalization phase is now underway.

We explored this transition in depth during the CMO Roundtable at the Agentic Distribution Summit.

Full recording: https://lnkd.in/d2RmchmU 

Gainsight Salesloft Momentum.io Metadata Amoeba AI Vivun N.Rich Fullcast Dana Consulting (NYC) Meerkat, Inc. Alysio RevSure AI Nooks Averi Salespeak.ai Greaser Consulting HG Insights Qualified ZoomInfo Demandbase Descript Common Room

#agenticdistribution

“What’s your reason for raising money? What’s your reason for standing on a stage and saying, ‘This is what our business does’? 

That should be reflected in your SEO – not just, ‘This is our primary keyword and we want to rank for it,’ but in how your business actually creates value.”

Eli Schwartz

Mark Roberge is betting on a reversal:

→ 90% of a rep’s time spent selling.
Through agents.

Let’s look at the history of this decline:

• 2018: Reps spent 36% of their time selling
– Salesforce State of Sales, 3rd Edition

• 2022: Dropped to 28%
– Salesforce State of Sales, 4th Edition

• 2024: Fell below 25%
– Salesforce State of Sales, 5th Edition

Despite billions in RevOps, tooling, and training, every GTM org is still paying 100% of the cost for 25% of the job.

Do you believe this trend reverses?
Or does AI replace the seller entirely?

Gainsight Salesloft Momentum.io Metadata Amoeba AI Vivun N.Rich Fullcast Dana Consulting (NYC) Meerkat, Inc. Alysio RevSure AI Nooks Averi Salespeak.ai Greaser Consulting HG Insights Qualified ZoomInfo Demandbase Descript Common Room

#agenticdistribution #agenticscaling #ainativegtm

Every era of GTM has a defining innovator.

In the automation era, that innovator was Manny Medina. With Outreach, he transformed sales execution, replacing manual outreach with scalable, automated workflows. It reset how revenue teams operated and created a multi-billion-dollar category.

Now, in the agentic era, Manny is doing it again with Paid.

The SaaS seat, the unit of value for 25 years, is collapsing. Pricing tied to humans no longer maps to a world where agents run execution. Manny is introducing the successor metric: Human Equivalent Value (HEV). HEV measures the throughput an agent delivers relative to a person.

This changes the foundations of SaaS:
• Pricing based on seats becomes pricing based on execution
• Forecasting shifts from ARR per headcount to HEV per workflow
• ROI is evaluated on throughput, not licenses

Automation was the first reset. Agentic distribution is the second. And once again, Manny is at the center.

On Sept 17 at 9am PT, he will open the Agentic Distribution Summit, sharing why HEV is the new benchmark and how GTM leaders must re-architect for an agent-led economy.

Attend free: https://lnkd.in/dXjE_Vuw

Gainsight Salesloft Momentum.io Metadata Amoeba AI Vivun N.Rich Fullcast Dana Consulting (NYC) Meerkat, Inc. Alysio RevSure AI Nooks Averi Salespeak.ai Greaser Consulting HG Insights Qualified ZoomInfo Demandbase Descript Common Room

#agenticbilling #saas #ai

AI’s new moats start where usage becomes memory.

AI-native startups are scaling faster than any generation of companies before them. But speed alone doesn’t create category leadership. 

The question is: what makes it last?

Since 1994, roughly 70% of tech value creation traces to network effects. In the AI era, where and when those effects emerge is shifting. – NFX

“The battle between every startup and incumbent comes down to whether the startup gets distribution before the incumbent gets innovation.” – Alex Rampell, a16z. 

Pete Flint (NFX) argues for a layered approach: “Your startup should be like a motte-and-bailey castle” with fast, early advantages giving way to deeper, harder-to-replicate defenses. 

At the Agentic Distribution Summit on Sep 18 at 1 pm PT, our VC Roundtable: AI-Native Network Effects and Defensibility will examine what actually compounds today.

What we'll cover: 
– How defensibility should be sequenced across an AI company’s lifecycle
– Which new defensibilities are emerging beyond SaaS-era moats
– How to distinguish viral growth from true network effects at the earliest stages

> VC roundtable – AI-Native Network Effects and Defensibility
> Hosted by Kathleen Estreich, Partner, Pear VC
> Sep 18 • 1:00 pm PT 

Featuring:
– Madhan Arumugam Ramakrishnan, Global VP, Support & Solution Engineering, Snowflake
– Valerie Osband Mahoney, Principal, NFX
– Jacob Effron, Managing Director, Redpoint 
– Jeremy Kaufmann, Partner, Scale Venture Partners

Join us free/ virtual: https://lnkd.in/d2RmchmU 

Gainsight Salesloft Momentum.io Metadata Amoeba AI Vivun N.Rich Fullcast Dana Consulting (NYC) Meerkat, Inc. Alysio RevSure AI Nooks Averi Salespeak.ai Greaser Consulting HG Insights Qualified ZoomInfo Demandbase Descript Common Room

#agenticdistribution #agenticgtm #networkeffects #aidefinsibility #gtm #innovation

25% of 6sense’s pipeline now originates without human touch.

Next week at the Agentic Distribution Summit, Latané Conant (she/her) (CMO, 6sense) joins Allison J. Snow (Founder, Salacia Go-To-Market Advisory, ex-Forrester) for a session on Designing AI Workflows That Sell Themselves.

Here are a few of the questions we’ll explore:

(1) Personalization vs. Context
Why “knowing someone’s industry” isn’t enough and why context is a more reliable driver of engagement.

(2) From Signals to Pipeline
How to translate trillions of signals into real outcomes without overwhelming GTM teams.

(3) Orchestration in Practice
What orchestration means in 2025 when execution spans sales, marketing, and RevOps.

(4) Change Management
How teams adapt when AI doesn’t just inform execution but begins booking meetings.

(5) Balancing Autonomy and Control
How to design workflows where agents drive action while humans maintain oversight.

September 18, 8:30am PT
Free and virtual | link to sign up in comments 
Hard Skill Exchange

Gainsight Salesloft Momentum.io Metadata Amoeba AI Vivun N.Rich Fullcast Dana Consulting (NYC) Meerkat, Inc. Alysio RevSure AI Nooks Averi Salespeak.ai Greaser Consulting HG Insights Qualified ZoomInfo Demandbase Descript Common Room

#AgenticDistribution #AI #AgenticGTM #GTM #Innovation

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